Book Description

No scientific quest is as exciting and elusive as the search to understand the Universe.Falk's book places this search in its historical context, tracing the quest from its roots in ancient Greece to the twenty-first century, through the breakthroughs of Newton, Maxwell, and Einstein, up to the excitement of "string theory" and today's efforts to merge quantum theory with general relativity.With as much emphasis on history as on science, Falk's enlightening and entertaining book is aimed very much for the general reader.The search for a Unified Theory is full of quirky personalities, interesting tales, and moments of brilliance-high science and high drama. ... Read more

Reviews (4)

on science, simplicity, and the quest for truth...
Dan Falk's Universe on a T-Shirt is an informative and entertaining tour of mainstream science-from Democritus to string theory-guided by a single, reining principle: that science is the pursuit of an aesthetic of simplicity, and that the culmination of this pursuit, the theory of everything, will be simple enough to grace a t-shirt.

Written in clear, clever, friendly prose, the book is easy to understand yet thorough; it serves as an excellent introduction for novices in the topics of physics and cosmology, but is full of fun facts, amusing anecdotes, and intriguing insights for the more knowledgeable reader. History is brought to life through brief biographical portraits of each scientist and thinker who has played a key role in the ongoing search for the ultimate theory, and the reader emerges from Falk's journey with an exciting sense of not only what is going on in science, but of what science itself is all about.

Speckled with illuminating quotes from physicists working in the field, Universe on a T-shirt dares to ask not only where physics is headed, but whether or not it is headed down the right path. Should notions like beauty and simplicity necessarily pave the road to truth, Falk asks. And will the ultimate theory mark the end of physics? Falk doesn't cower from the philosophy that lurks at the heart of physics. Instead, he embraces it, and allows the reader to delve into some of the most fundamental questions about the nature of reality. The author sympathetically writes of the layman's sense of cosmic alienation-perhaps this book can help those afflicted feel at home in the universe, and a part of the inspiring quest to truly understand it.

Entertaining but lacking
First I'd like to point out that I am one of those readers who have read the popular books of many of the cosmologists and physicists mentioned in this book. And I agree with a previous reviewer that if you have read Martin Rees and John Barrow, this might not be a very interesting book.

But I had a good time reading it. It is short and concise. Lots of chapters (I think the longest is about 5 pages or so) which makes this a very easy book to read.

The main problem is that the task of crunching the search for a "theory of everything" through the ages into a book of about 200 pages is impossible. That is probably why this is a book with no mention of anything but "western" theories.

I also found the last chapter on where God is in everything rather confusing. It seems as if the book's editor wanted to cut it but it was left in as some sort of compromise. It provides an afterthought but takes the narrative off track.

Dan Falk has written a good book for lay people who find Stephen Hawking inaccessible and who don't feel at home with more theoretical books. But the entire concept of "putting theories on a t-shirt" which every section ends with, says a lot about this book: simplification is king. And that is why it only gets three stars from me.

If you would like to read a really good book about scientific history, read Mendeleyev's Dream by Paul Strathern. It is everything this book is not.

Good attempt by a journalist.
By my standard only three stars, but it does not mean book is bad. This is a brief history of science that led to creation of modern cosmology and our current knowledge of the Universe. Not for Scientific American readers though.
Book targets general population, people who read about Cosmos and science in daily newspapers.
Written nice and easy, but advanced reader who studied works of scientists like Brian Greene, Lee Smolin, John Barrow, Martin Rees or Steven Weinberg, should not bother.

For discussion about religion and science (do we have God-designer or not?) it is better to check Victor Stenger's "Has Science Found God".
Also, a good alternative is Timothy Ferris: "Coming of Age in the Milky Way" - same topics.

No jacket (or physics degree) required...
"Universe on a T-Shirt" is perfect for anyone who wants a concise, easy-to-read guide to one of the great quests of human civilization: the search for the ultimate laws of physics -- the "Theory of Everything." This quest ranges from the speculations of the Greek philosophers, through relativity, quantum mechanics and the latest developments in string theory. These are forbidding subjects for many physicists let alone the interested layperson, but science journalist Dan Falk has managed the difficult task of getting across their basic ideas, and wider significance, in an entertaining way. The science is leavened with just the right amount of human interest and historical detail. The book is well illustrated with black & white photos, diagrams and cartoons, and includes a recommended reading list for those who want to explore further. It would make a great gift for a high school student interested in science. ... Read more

Book Description

Chaotic dynamics has been hailed as the third great scientific revolution in physics in this century, comparable to relativity and quantum mechanics. In this book, Peter Smith takes a cool, critical look at such claims. He cuts through the hype and rhetoric by explaining some of the basic mathematical ideas in a clear and accessible way, and by carefully discussing the methodological issues that arise. In particular, he explores the new kinds of explanation of empirical phenomena that modern dynamics can deliver. Explaining Chaos will be compulsory reading for philosophers of science and for anyone who has wondered about the conceptual foundations of chaos theory. ... Read more

Reviews (2)

A Complete Text for System Identification
This book is very through in presenting methods of system identification...mathematically.However as with most good mathematical oriented books there are not a lot of practical design type problems.One other mark aginst the book is that similar notation is used for different topics, which can sometimes be a bit confusing. One thing I might recommend, to a potential buyer is that you take a course in random process, and possess a through understanding of signals and transforms.All in all though if a little more meat in terms of practicality were added I'd rate this book a five.

excellent book
An excellent textbook for engineers, and a necessary reference for Matlab toolbox (System Identification). ... Read more

Book Description

At the heart of modern cryptographic algorithms lies computational number theory. Whether you're encrypting or decrypting ciphers, a solid background in number theory is essential for success. Written by a number theorist and practicing cryptographer, Cryptanalysis of Number Theoretic Ciphers takes you from basic number theory to the inner workings of ciphers and protocols.First, the book provides the mathematical background needed in cryptography as well as definitions and simple examples from cryptography. It includes summaries of elementary number theory and group theory, as well as common methods of finding or constructing large random primes, factoring large integers, and computing discrete logarithms. Next, it describes a selection of cryptographic algorithms, most of which use number theory. Finally the book presents methods of attack on the cryptographic algorithms and assesses their effectiveness. For each attack method the author lists the systems it applies to and tells how they may be broken with it.Computational number theorists are some of the most successful cryptanalysts against public key systems. Cryptanalysis of Number Theoretic Ciphers builds a solid foundation in number theory and shows you how to apply it not only when breaking ciphers, but also when designing ones that are difficult to break. ... Read more

Reviews (2)

Good textbook for graduate and advanced undergraduate course
I read the book and is almost self contained. No knowledge in Number Theory is assumed. Has a great combination of text and math. Last few chapters could have been better.

Assistant Researcher
An excellent book. I am a beginning cryptographer with some statistics, discrete math, user level crypto and programming under my belt - crossing over from another field. This book is an excellent read with proper amounts of examples and theorems. It is easy to follow and would make a good reference. ... Read more

Book Description

"SCIENCE JOURNALISM AT ITS BEST. . . An impeccably researched, amazingly up-to-date, crisply written and well-illustrated survey."
--Nature
At the cutting edge of the sciences, a dynamic new concept is emerging: complexity. In this groundbreaking new book, Peter Coveney and Roger Highfield explore how complexity in mathematics, physics, biology, chemistry, and even the social sciences is transforming not only the way we think about the universe, but also the very assumptions that underlie conventional science.
Complexity is a watchword for a new way of thinking about the behavior of interacting units, whether they are atoms, ants in a colony, or neurons firing in a human brain. The rise of the electronic computer provided both the key and the catalyst to our exploration of complexity.
A new generation of computers that runs on light and exploits the bizarre properties of quantum mechanics promises to deepen our understanding still further. The advances we have already witnessed are spectacular. The authors take us inside laboratories where scientists are evolving the genetic molecules that enabled life to emerge on earth and generating universes teeming with virtual creatures in cyber-space. We witness the utterly realistic behavior of a school of virtual fish--computer-generated replicas that have been trained to swim gracefully, hunt for food, and scatter at the approach of a leopard shark.
Compelling in its clarity, far-reaching in its implications, vibrant with the excitement of new discovery, Frontiers of Complexity is an arresting account of how far science has come in the past fifty years and an essential guide to the rapidly approaching future.
"[A] MARVELOUS AND COMPREHENSIVE WORK . . . Virtually any scientist or interested lay reader will find this book engrossing, edifying and inspiring."
--Publishers Weekly (starred review)
... Read more

Reviews (5)

Frontiers of Complexity
Peter Coveney and Roger Highfield, coauthors of The Arrow of Time: A voyage through science to solve time's greatest mystery, performed comprehensive work explaining the evolution of the science of complexity.

The authors examined the concept of complexity in such scientific disciplines as mathematics, biology, chemistry and physics.

The authors traced and illustrated the evolution (from reductionism) of complexity in the works of such scientists as:

Charles Babbage - English mathematician, a celebrated icon in the prehistory of computing. Invented Difference Engine No. 1. The Charles Babbage Institute is an historical archive and research center of the University of Minnesota.
George Boole - Better known for the algebras named after him, and as one of the pioneers of modern logic.
Kurt Godel - First to demonstrate that certain mathematical statements can neither be proved or disproved.
Richard Feynmann - Nobel laureate, introduced "universal quantum simulator".
Stuart Kauffman - Author of At Home in the Universe: The search for the Las of Self-Organization and Complexity.

The authors also emphasized the beginnings and advances in computing through the pioneering works of:

John von Neumann - Invented a self-reproducing automation to show how machine could perform the most basic function of life - reproduction. He is known as the "father of artificial life."
Allan Turing - His work on computers and their relationship with brains made him the "Father of Artificial Intelligence."
John Hopfield - Showed that there is a mathematical mapping of the Sherrington-Kirkpatrick spin-glass model onto a simple type of fully connected neural network model called Hopfield network.

What I got from this book:

Nothing interests me more than artificial intelligence in my brief exposure to the science of complexity. This book dealt with neural networks so much, I just loved it. On the other hand, its too little - just enough to keep me craving for more!

The foreword by Baruch Blumberg, Nobel laureate, left me with a robust and distinct message that I would like to share with you, and I quote: "Each time an experiment is performed to test a hypothesis, more questions are revealed; there is no limit to the mysteries of nature and to our desire to understand them. The study of complexity offers an opportunity to stand back and consider the global interactions of fundamental units - atoms, elementary particles, genes - to create a synthesis that crosses the borders of scientific disciplines, to see a grand vision of nature.

Response to other reviews
Alright, seeing "this book should be on the shelf next to Roger Penrose's 'The Emperor's New Mind' and James Gleick's 'Chaos'", and another review saying that the book denies Godel's Theorom, confused me for a while. Then I realized that the latter refered to nueral nets. Assuming that the nets referred to are analog, there is no contradiction. Godel's Theorom proved the incompleteness of formal language systems, a.k.a. digital systems, which constitute a smaller information set than analog systems. Mathematically, analog systems do not meet the neccessary conditions for Godel's Proof to apply. However, the claim to 'completeness', if it be made, is ungrounded. Analog systems simply represent a higher information dimension, not an infinite information dimension.

Excellent Primer on Complexity
This book will give you some genuine insight into the emerging (no pun intended) field of Complexity. It presents historical and current research in a way that allows both the researcher and informed layman to get a good grasp on the concepts presented. Both provocative and educational its only flaw is a perhaps too doctrinaire belief that Complexity is the "next step" in science instead of another branch. If you want a good in-depth view of the current state of Chaos and Complexity theories without having to learn all the math this book will give you what you need. It belongs on the shelf next ot Roger Penrose' "The Emperors New Mind" and Gleick's, "Chaos".

Good beginning, iffy second half.
This book starts off well enough, with a fascinating chapter on the limits of mathematics, focusing on Godel's refutation of formalism (the idea that the whole of mathematics can be derived from a set of logical statements), followed by a brief history of computers and the computation. But once the authors begin their explanation of complexity, they come off as smug and overzealous about their field. They seem to take every opportunity to belittle other fields of science, and try to convince us that complexity will provide the ultimate explanaion of every facet of the universe, from biology to physics to chemistry to social sciences.

This may sound like an exaggeration, but it really isn't: at the beginning of their chapter on complexity in chemical reactions, they dismiss the idea that chemistry (and by extension, biochemistry) can be explanied by quantum physics because the calculations it requires are too complicated. I understand that it is difficult to use quantum physics, and that its effects are only significant on the atomic level, but that does not mean that quantum effects do not exist! The chapter on chemistry marks the end of any reasonable explanation of complexity, and by end of the book complexity is almost completely forgotten, as the writing gushes on about neural networks and aritficial life.

It is these later chapters on life and aritificial life that are the most poorly written. The authors commonly say things like "It is becoming clear that obstacles to creating aritfical consciousness may not be as formidable as we had thought", yet provide little proof of this. They basically claim that neural networks are only a few innovations away from becoming fully funcitoning human brains, but they provide a one-sided explanation of their usefulness and fail to mention their failings, especially in cognitive science (which is the study of the brain, of all things). They strongly hint that current ALife programs are creating new life, when they are pretty must just clever programs that manipulate computer memory according to a set of rules. They just don't seem to realize that simulating certain aspects of life with computers and life itself are very different things! We are not even certain that neurons are the basic building block of the brain, yet they are claiming that we now know enough about the brain to create a computerized one in no time. Their argument is very smug and one-sided: the only time they ever mention a criticism to current ALife and AI practices is when they present Roger Penrose's very reasonable hypothesis about how computers cannot simulate intelligence in large part due to their reliance on mathematical logic, which, as Godel proved, can sometimes break down. Yet they quickly dismiss this view, seeming to think that Godel's theorems are nothing more than irrelevant parlor tricks. Their claim that a neural network can be taught to do anything, and therfore can overcome Godel's theorems, is especially poor: we could never teach a human brain to fly, for example, because it (and the body it is in) are not equipped to do this. So why do they think that our arcane artificial neural networks are equipped to create consciousness?

Despite this heavy criticism, however, this book is still quite interesting if you are new to complexity, chaos, and artificial life. The author's overexcitement about their field seems to be common when new branches of science emerge, like when AI was first getting off the ground. If you read this book, just realize that its bold claims may be grounded in false hope.

An introduction to complexity for the intelligent reader
Complexity is a new field that touches on almost every one of the sciences, and delivering a solid overview without being superficial is an exceedingingly difficult task; authors Coveny and Highfield have created a book that manages just that. They cover the physical, computational, biological and cognitive sciences, in each case with enough detail to really convey the essence of the field while still remaining very readable to the non-specialist reader. (There's a very detailed- and entertaining- annotated bibliography for those looking for more detail.)

While there are currently a number of very good non-technical introductions to complexity theory by such skilled authors as John Casti, Mitchell Feigenbaum and others, this particular volume may well be the best of an excellent lot. Highly recommended to anyone looking for a a non-rigorous, but non-trivial, introduction to the field. ... Read more

Book Description

Semiotics, a well established discipline of signs and their use in human and computer communications, is increasingly recognized as important to understanding information systems and computing in general. This important new resource examines a set of semiotic methods for information systems development. Kecheng Liu offers well balanced coverage of recent theoretical investigations and practical applications. He introduces the MEASUR approach for requirements elicitation, analysis, and representation and illustrates the methods in three major case studies. In these cases he demonstrates how information systems can be developed to meet business requirements and to support business objectives. ... Read more

Reviews (1)

Recommended for acim's lovers
This book starts with an introduction to ergodic theory. The rest of the book is on absolutely continuous invariat measures and their applications. This is one of the best books that studies conditions of existance of absolutely continuous invariat measures for piecewise expanding maps. ... Read more

Book Description

Over the last two decades, chaos in engineering systems has moved from being simply a curious phenomenon to one with real, practical significance and utility. Engineers, scientists, and mathematicians have similarly advanced from the passive role of analyzing chaos to their present, active role of controlling chaos-control directed not only at suppression, but also at exploiting its enormous potential. We now stand at the threshold of major advances in the control and synchronization of chaos for new applications across the range of engineering disciplines.Controlling Chaos and Bifurcations in Engineering Systems provides a state-of-the-art survey of the control-and anti-control-of chaos in dynamical systems. Internationally known experts in the field join forces in this volume to form this tutorial-style combination of overview and technical report on the latest advances in the theory and applications of chaos control. They detail various approaches to control and show how designers can use chaos to create a wider variety of properties and greater flexibility in the design process. Chaos control promises to have a major impact on novel time- and energy-critical engineering applications. Within this volume, readers will find many challenging problems-yet unsolved-regarding both the fundamental theory and potential applications of chaos control and anti-control. Controlling Chaos and Bifurcations in Engineering Systems will bring readers up-to-date on recent development in the field and help open the door to new advances. ... Read more

Book Description

A renowned mathematician shows how the "science of surprise" can help explain some of the most inexplicable phenomena in science, nature, the arts, the economy, and more. ... Read more

Reviews (3)

Good intro to some complex ideas
I found this to be an easy to read introduction to current hot topics in science and math. Catastrophe theory, Complexity, Chaos, and emergence. There is also an excellent listing of resources with commentary in the back of the book, called, "to dig deeper". I am an engineer with an MBA, so found a number of the examples very interesting. For the curious, (or less technically adept), this is very well written. Mr. Casti goes quickly from theory to "real world" examples. His illustrations are also very helpful to understanding the basic principles. Most books on complexity contain way too much math for the average reader, or are very simplistic, "Ubiquity" as an example. I think you will find a nice balance here.

Crap. Total crap.
Forgive me for the inarticulate title, but that about sums it up. In this book, John Casti uses misleading chapter titles and open-ended explanations to new scientific theories to explain what he thinks should be the foundation of the "science of surprise".

Now, don't get me wrong: open-ended material is not always a bad thing. Especially with new theories on chaos and related subjects that have not yet been given a strong leg to stand on; it is great to give readers a little insight so they can come up with some of their own conclusions. But there is a difference between presenting an interesting question then suggestion some well-thoughtout solutions and presenting an interesting question and jotting down a quick answer by using unproven assumptions.

One example of this is when he explains the irrationality of common sense and bases almost his entire argument on the fact that many people will take $100 dollars today instead of $120 dollars next week and $1,300,000 in a year instead of $100 today. If you read that whole chapter, you will find little more than this explaining why common sense is a faulty way of thinking other than an accident made by an unattentive engineer. Granted, I agree (for my own reasons), but these two situations are not a very good explanation for why common sense in decision making is unwise.

And from what I read and skimmed through, basing solutions off of unstable assumptions and unique situations seems to be what Casti is best at. He uses many words to explain some of the simplest theories in this scientific genre and too few words for the most complex. His thoughts hold little order and several times chapters and paragraphs don't even finish the thoughts that he starts.

I am giving it two stars because eventually he does correctly rattle off some of the basic theories, and he includes a couple of interesting situations and questions.

If you want a good read from the area of unpredictable science, try Chaos : Making a New Science by James Gleick.

Some interesting points, but very uneven.
While parts of this book were very thought-provoking, too many details were either left out or skimmed over to allow this book to stand alone. For example, the formula the author supplies to calculate the eccentricity of a simplex couldn't possibly produce the results he gives in the adjoining table; some are infinite, and the formula as he states is specifically designed to avoid such results. If you're really interested in catastophe theory or chaos theory, make sure you read this book where you have other reference materials on hand. ... Read more

Book Description

Everyone knows the small-world phenomenon: soon after meeting a stranger, we are surprised to discover that we have a mutual friend, or we are connected through a short chain of acquaintances. In his book, Duncan Watts uses this intriguing phenomenon--colloquially called "six degrees of separation"--as a prelude to a more general exploration: under what conditions can a small world arise in any kind of network?

The networks of this story are everywhere: the brain is a network of neurons; organisations are people networks; the global economy is a network of national economies, which are networks of markets, which are in turn networks of interacting producers and consumers. Food webs, ecosystems, and the Internet can all be represented as networks, as can strategies for solving a problem, topics in a conversation, and even words in a language. Many of these networks, the author claims, will turn out to be small worlds.

How do such networks matter? Simply put, local actions can have global consequences, and the relationship between local and global dynamics depends critically on the network's structure. Watts illustrates the subtleties of this relationship using a variety of simple models---the spread of infectious disease through a structured population; the evolution of cooperation in game theory; the computational capacity of cellular automata; and the sychronisation of coupled phase-oscillators.

Watts's novel approach is relevant to many problems that deal with network connectivity and complex systems' behaviour in general: How do diseases (or rumours) spread through social networks? How does cooperation evolve in large groups? How do cascading failures propagate through large power grids, or financial systems? What is the most efficient architecture for an organisation, or for a communications network? This fascinating exploration will be fruitful in a remarkable variety of fields, including physics and mathematics, as well as sociology, economics, and biology. ... Read more

Reviews (3)

Inspiring
The author believes that human thought might be a small world, in the sense that one could reach any idea if he/she finds the right associations and "short-cut"s. The small-world theory is indeed one of those short cuts itself. It links many different domains and uncovers some interesting common behavior.

The theory is developed in a scientific manner with extensive numerical support. Rich literature reviews and many open questions make this book a good research reference. Complex observations are generally followed by qualitative explanations. However, some of the simpler derivations are not fully clear. I believe that adding a few lines here and there can turn this book into a textbook.

The book spans many different areas of science and a deep understanding of the related results may require some background. However, each chapter ends with a brief summary, allowing the reader to move forward if he/she finds the chapter difficult. In summary, as the author puts it, the book is simply the "end of the beginning" in an exciting new field.

Great scientific synthesis
The book takes a systematic look at the 'small world' graphs. These natural graphs have been discovered by graph theoretist as erly as 60's, but were not properly understood. The graphs are remarkable in their ability to cluster and scale lengths. There are fundumental connections between these graphs and complex systems, discrete dynamical systems, computation and information processing. Duncan has done a tremendous job in building experimetal and theoretical models trying to understand how these graphs come about and sustain themselves. Read this book.

Not as wide ranging as the reviews led me to believe
I read the review in New Scientist, and liked the sound of this book. When it arrived I read the blurb on the back, and was further encouraged by the fact that a Sociology Professor was encouraging students to read it. I was therefore expecting a reasonably tough but rewarding read (my math is at undergraduate level and somewhat dated, but I do make an effort). Instead with the exception of a few pieces of commentary, particularly at the beginning, I found the book virtually impenetrable because of the denseness of the mathematical modelling techniques used. I suspect this is one strictly for the experts, and those with excellent post-graduate math skills. ... Read more

Reviews (1)

First statistics book on chaos
This book comes out with much anticipation from two of the world-renowned experts on nonlinear time series. Indeed, the once superhot chaos theory in physics and math in the 80s was only introduced to statistics by Howell Tong in his 1990 book on nonlinear time series, Tong and R. L. Smith's 1992 RSS Chaos Day workshop and subsequent JRSS B special issue on chaos and L M Berliner and others's 1992 review articles in Statistical Science. Now 10 years after, what has achieved in between and what has not materialized as once seemed so promising? There are several PhD theses written in this area and there are continuing applications of chaos theory in science, from physics, mechanics, atmospheric sciences to biomedical and physiological data analysis. We can safely say that chaos theory is probably just another area or another tool that one can use to understand or interprete apparent randomness in simulations or in observed data. With purely stochastic tools that are dominant in modeling high-dimenional and un-parameterizable processes, chaos theory provides the crucial link between deterministic and computer modeling, and uncertainty in observed output and model simulations. Maybe with the ever closer collaboration between statisticians, mathematicians, and physical scientists in understanding and using the most daunting PDE and large scale models or computer models, chaos theory may finally come to be appreiated more by statisticians, who have traditionally been over-concerned with modeling noise, while overlooking modeling the overall deterministic patterns and structures in data.

Finally, some words about the book itself. I think it is a fairly comprehensive survey on the statistical work in the last decade, though understandably it is biased toward the authors' own research and collaborators' work. I think in order for it to be used as a textbook, it needs to be supplemented by a more balanced account of other aspects of chaos theory, such as geometrical theory and dimension reduction techniques. For example, the review chapter of dimension theory by C. Cutler in a book edited by H. Tong himself in 1990 (published by World Scientific) and Michael Kirby's recent book: Geometric Data Analysis: An Empirical Approach to Dimensionality Reduction and the Study of Patterns. The significance of fractal geometry theory on multivariate data analysis and time series statespace when the vector may lie on an manifold or lower-dimensional intrinsic space has recently been demonstrated by Z.Q. Lu in Nonparametric Regression With Singular Design in J. of Multivariate Analysis 1999, vol. 70, pp.177-201. It appears that the potentials of chaos theory for motivating newer statistical techniques and developing new statistical theory to understand better deterministic systems and related data analysis remain to be explored. In conclusion, I warmly recomend this book to next generation students and time series lovers, and to scientists who might be wondering what statisticians are up to in this important area. ... Read more

Book Description

Reviews (7)

Engagingly Written Science
Roger Lewin engagingly writes of his discussions with leaders in the field of complexity, the study of non-linear, dynamical systems in the life sciences. Studies in 'chaos' theory and related fields like cellular automata have led to new formulations of self-organization and non-vitalistic emergence in living systems. Although still considered a fringe element by some of their colleagues, people like Stuart Kauffman, Chris Langton, Norman Packard and others are exploring models of "...common dynamical patterns in the realms of physics, biology, and society..." (193) which may radically change our understandings of evolution and consciousness. A cheering trend toward non-aristotelian directions.

Why read complexity?
I am not a scientist. I am, however, interested in a wide variety of subjects and fascinated by complexity. I am not referring now to the book, or the subject but the expression in the real world of all that there is to know and understand. How can anyone live and not recognise at the deepest levels of their understanding that everything that exists does so in dependence on other things that exist and that this interdependence, because of the number of dynamic variables, cannot be described otherwise than a complex system. It is at this point that anyone who has read the book or who is a part of this book will protest that I have missed the point. I have not. This book isn't about a vague subjective comprehension of all things being related. It is much more scientific than that. I have started off this way because I am aware that in the hustle of everyday life-the place where most readers of books reside-the subject of the science of complexity is beyond even the periphery of what might occur to them as a topic to take an interest in, let alone find relevant. Having a general, non-expert appreciation for the immense complexity of which we are a part is an appropriate mindset to bring to any reading of the subject. The book is deserving of a wider appeal than for just new wave idea groupies.

I find Lewin strikes the right balance with his reader presenting difficult concepts with elegant clarity yet providing enough detail to challenge the reader. To make the material too simple would leave the concepts incoherent-to provide too much would leave the reader behind. He also presents a balanced view of the subject. There are detractors in the scientific community. They are heard from. Lewin develops various concepts directly related to complexity rather cleverly. We are given a piece of concept that is added onto later in a different context providing us with a kaleidoscopic way of thinking of the material. It is all connected but our focus shifts slightly giving us a new view of the subject. In the beginning there were Boolean Networks. Other concepts follow: edge of chaos; complex adaptive systems; emergence. If anyone has ever wondered even in passing why is it that discrete bits of biota or data that do not amount to much in themselves can produce not only something more complex when put together but something that is more than the sum of its parts then Complexity is of interest to you.

This book doesn't have to be the final authority or explain it all to be a very good read. And, in reference to other reviews, novel new ways of approaching scientific inquiry don't come from just anyone. Personalities matter. Putting the subject of complexity in the context of those who have been pursuing its secrets is not only acceptable but adds to our understanding. The implications for the opening up of new ways of seeing what we've heretofore been looking at 'through a glass darkly' are incredible. I can see why some of the leading scientists might find the subject worth their time and energy. So many things we wish to fix about how we operate within the system that supports us have proved intransigent to change. Perhaps this is because up to now we have been hampered by a too narrow view of what dynamics are relevant to a particular line of inquiry.

Lewin has presented complexity as a good mystery novel. It is a non-fiction mystery novel the ending of which has yet to be written.

A fine SECOND book on Complexity
The scope of complexity science is vast, encompassing many disciplines. This book focuses on how the new idea of complexity relates to biology by discussing the idea with many leading biologists of the day. Other reviewers were put off by the book's lack of definition of what complexity is, and the lack of resolution as to what terms such as "edge of chaos" mean. But that is exactly the point. These terms do not have clear definition today. Complexity is a very immature field, frequently pursued at the visceral level. It is hard to define what it *is*, but frequently easy to identify it where it exists. I can understand the other reviewers' concerns with the lack of definition, and can only suggest that because of the narrower focus (biology), this is an appropriate second book on complexity.

As a second book, narrowly focused on the question of complexity in biology, it is outstanding. Specifically, the question is one of how self-organization (complexity) relates to evolution and what this means for natural selection. Complexity is frequently talked up as the unifier of the sciences. Lewin takes a balanced approach, taking the time to talk to complexity theorists and understand their ideas, then talking to mainstream biologists to see how the ideas relate. His conclusion shows no inherent bias. Where other books on complexity show extreme (perhaps undue) enthusiasm, Roger Lewin's concusion is decidedly "wait and see". I found his insights to be on target and relevant.

I mentioned that this is a good second book. For an introduction to complexity, read John Holland's "Hidden Order". For a history of the Santa Fe Institute and some of the personalities there, read Mitchell Waldrop's "Complexity". Either or both of these would serve as an adequate introduction to this book.

Rock Star Drivel
I'm amazed that this book is still out there. This reads more like People magazine than Popular Science. The book is a poor introduction to the science of complexity, or to science itself, because it focuses on people not ideas, and (as another reviewer wrote) the ideas are not well defined. If you must read it, read it as a treatise for now not to report science and why the towers of academic institutions remain coated with ivory. Treat yourself to a bite of ice cream everytime a real complexity-related fact is offered. I don't think you'll be off your diet.

A big disappointment
Lewin fails to clearly define what complexity and chaos mean and the jocular, conversational style of this book never actually brings things in to focus. Much is made of "the edge of chaos" yet it is never actually defined or examplified. What examples exist are simplistic and only erode and hide what ever the point may be. ... Read more

Book Description

In the coverage of dynamics, there is a definite gap between ``picture-book'' popularizations and the technical literature. This work fills that gap. Shows engineers and scientists how, by the application of statistical methods, coordinate transformations and mathematical analysis, any complex, unpredictable dynamical system can be mapped--transformed into a simpler, predictable system. The various modeling tools available, their benefits and their limitations are described. Examples and analogies are used in place of theorems and proofs, making this an immediately practical book. By showing how to make models more meaningful and useful, it will be particularly helpful in clearing up the impasse between economics and system dynamics. Features a number of carefully selected references to more mathematical treatments, examples of some of the more specialized techniques and case histories of some models. ... Read more

Reviews (4)

A masterpiece
This is the kind of book that should be available in every area of science and mathematics. A book that is not a research book, but yet is not a broad popularization. This book can benefit both persons who are just beginning a study of dynamic modeling and I dare say things will be learned by even those that are researchers in the area. Good work Foster Morrison whoever you are.

A broad overview
Very general overview for the subject of dynamic systems modeling, providing ample historical perspectives. Not suitable for folks looking for deep technical matters.

Best modeling book on the market !
This book is certainly the best book you'll find around for treating in depth the subject of modeling dynamic systems. The style is clear and very intuitive. It provides a well-structured identification of dynamic systems and explains the "what you can do and what you cannot" for modeling all types of dynamic systems. It's true that it can be hard to find but waiting some couple of weeks certainly is no reason for not trying to get this extraordinary overview of dynamic systems !

The only drawback you could find is that it is too short... reading it makes you want more...so using it as an introduction to dynamic systems can only motivate you at going further in the field of dynamic systems modeling !

Single best reference for "modern" applied modeling
This is a fantastic book and I'm sorry it's hard to get now. I found it by accident in a used book store in Madison, WI, in 1995 and found I learned a lot from it, even though by that time I had already taken multiple classes in Differential Equations, Linear Algebra, Statistics, etc. Dr. Morrison really sets out in lucid detail many of the important developments in applied modeling theory--dynamical systems, stochastic systems, the fudamentals that lie behind them--from a very useful perspective, and one that is often missing from the orthodox academic treatments. What he chooses not to cover in detail he references thoroughly. I wish that I had had this book when I was learning many of the topics. Anyone who is seriously considering learning dynamic modeling should read this book and I have little doubt that fairly experienced modelers will find something between the covers. ... Read more

Book Description

Jr/Sr/Grad course (one or two terms) in systems analysis and design. Core course(s) for IS majors. Most texts cover SAD using the "traditional" structured approach (Dennis: SAD). The Object-Oriented models have been growing in importance and the market itself is growing. ... Read more

Reviews (2)

Two Thumbs Up
Alan Dennis and Barbara Wixom make a difficult subject come alive with easy to understand language and real life case studies

Minimally Acceptable as a College Textbook
The authors take on a pretty broad topic, and give it just cursory overview. Their 16 chapters are divided into the broad areas of Planning, Analysis, Design, and Implementation. However, the individual chapters within the text are not well organized within those areas. For example, what are UML Class diagrams and structural modeling doing in the Analysis phase, when they more clearly belong in design? It seems like UML has been pasted into a systems book just so that a current buzzword can end up in the title. When was the last time any of you used CRC cards? Yet they end up in the same chapter with UML diagrams.

Chapter 10, System Architecture Design, is rather disappointing. Although the book mentions terrorist attacks, indicating its 2002 heritage, there is barely a mention of web-based deployment or eCommerce paradigms in this section.

Many of the anecdotes collected as side bars in the book are entertaining, but they don't always make a point relevant to the discussion at hand.

If this is your textbook for a class, pay close attention to the prof. You will get much better insights into System Analysis and Design from a real person with real-world experience, than this cobbled-together book. ... Read more

Book Description

"Outstanding... Signs of Life is a carefully crafted, readily understandable, and wise book. Biologists, chemists, physicists, and a wide audience will read it with delight and intellectual profit." --Stuart Kauffman, author of At Home in the Universe.

Signs of Life applies the mathematics of order and disorder, of entropy, chance, and randomness, of chaos and nonlinear dynamics to the various mysteries of the living world at all levels. This book is an entirely new approach to understanding living systems and will help set the agenda for biology in the coming century. ... Read more

Reviews (10)

Lots of figures and photos, very visual!
This book is very good because it shows you a very broad spectrum of phenomena in which emergence takes place (genetics, the brain, the ants, rainforests, virus, economics, etc.). Emergence happens when a system of simple and numerous parts does something you couldn't have predicted from a description of the parts. It's full of very well chosen examples of emergence in complex systems. If you don't understand what the science of complexity *really* is about, buy it! You certainly will understand after you read it, I can assure you.

I've always hated books in which there's only text and more text. I need drawings, diagrams, things that SHOW you something and make well explained ideas even better! This book is perfect in that. Also, if you don't like mathematics, they are exclusively inside gray boxes, and you just look at them if you want, the explanation is good enough. And by the way, the boxes are just great!

Excellent source of information...
This is what overviews of scientific fields of research should be like. The book begins in a gentle manner with an introduction into non-linearity, chaos and complexity. Many somewhat detailed technical steps are shown in text boxes and there are many illustrations to try to convey the information to a casual reader.

In fact, this book bridges the gap between general overviews (something like Gleick's "Chaos") and much more scholarly presentations ("Complexity : Metaphors, Models, and Reality"). I suspect some non-technical readers won't make it very far but that is more likely due to the fact that they spend too much time on things they don't understand. Many important aspects of complex adaptive systems in biology are reviewed using many different examples. Both theoretical and real-life examples are typically used to help make the point.

It is evident that the authors not only really understand the subject, they are also passionate and have excellent writing skills. Kauffmann is cited frequently but I suspect that most who have read "Investigations" will likely get a much better idea of his thesis when they read this book.

The only minor point: why no commentary on where we appear to be rushing? Or better yet, why nothing about the philosophical implications of complexity? Perhaps the authors wanted to keep this book as non-controversial as possible and thereby potentially have it as an "official" reference but I cannot see why people should be upset by drawing some conclusions. Unless, of course, it is simply because some of the conclusions are so scary.

This book should be standard reading!

How all the explanatory parts don't explain the whole
This book is filled with chapter after chapter of 'gee-whiz' factoids and equations about some interesting attempts to make some scientific sense out of the nature of biological systems. All the appropriate buzzwords: 'complexity', 'emergence', 'chaos', 'neural nets', 'fractals', and so on are amply represented. As a compilation or overview of the research efforts into these various areas, this book succeeds reasonably well. For this, it gets three stars.

They explain to us in the Preface, "The consistent theme that runs throughout...is the understanding of biological processes in terms of complex dynamics from which emerge characteristic patterns of order. The objective is to show how scientists are thinking in this area and what tools are available for understanding the creative process."

But, there is no concluding chapter, no summarization, no binding coherence beyond some vague sense of it all being somehow complex stuff, from ant colonies to brains to stock markets. All the different chapters convey their different messages and that is that. It all sounds important, highly scientific, cutting-edge, and intriguing. Gee, isn't it all amazing?

When it is all said and done, however, there is very little about biological systems that is actually explained by all these sexy topics.

An unintentional byproduct of this overview - what is most glaringly apparent when the dust settles and the mind clears - is the feebleness of all these efforts in making much of a dent in understanding life to any serious degree. And I think if there is one lesson to be taken away from this book, it ought to be that. For that feebleness makes a deep statement about the cogency of the application of the types of modalities presented to the problem of life, and about the notion of 'emergence' in general as being a computational problem.

Order for free
If you've ever been in a traffic jam, chances are, you've also engaged in a coordinated, complicated activity with other drivers - without even knowing about it. They are called traffic density waves. How can that be? How can you engage in large-scale behavior and not know it? It happens because of emergent behavior that results from simple algorithms in our driving. It happens to you, just like it happens to ants, bees, and termites. These simple rules result in unexpected, large-scale order. It's what Sole and Goodwin would call "order for free."

Sole and Goodwin begin with one of the best introductory summaries that I've seen of simple chaotic behavior in nonlinear systems. The interesting thing about these systems is the way in which complicated behavior results from repetition and feedback using simple rules.

Later descriptions of biological systems carry this theme forward, and constitute some of the most interesting reading in this book. For example, in the chapter on "Ants, Brains, and Chaos," the authors describe a model that simulates the raiding patterns of army ants. Observing these insects from a distance, one might be inclined to wonder at the appearance of a higher purposeful component to the movement of colony. With simulations, however, the authors have argued convincingly that the basic patterns seen in the foraging of army ants result from relatively simple algorithms built into the individual insects. These simple algorithms, at the individual level, result in large-scale behavior that has no obvious causal connection to the algorithms that are their cause.

A similar chapter on the human brain helps us see that our own intelligence is most likely the amazing consequence of emergent behavior resulting from the interconnections and interactions of an unimaginable number of connected neurons in our brains. As such, it begins to make sense that what we call "ourselves" is really an emergent property of cells that is as unrelated to individual members as the marauding patterns of army ants is to the simple algorithms operating on the level of individual insects.

Yet another fascinating example from the insect world is that of mound-building termites and nest-building wasps like those that infest my barn each year. Again, with computer simulations, the authors illustrate that beautiful wasp-like nests can be created using automata with simple algorithms that belie the complexity of the structures that emerge from groups operating under simple rules.

After reading page after page of examples, one begins to get the sense that self organization is a rule of nature. It seems to be everywhere - almost to the degree that we might marvel when it does not appear. This, I believe, is one of the underlying messages in "Signs of Life:" That the order and complexity we perceive is actually the result of simpler algorithms operating in (mostly nonlinear) systems with feedback. That there is a broad range of emergent properties that can, and often do, result from such systems. The authors also argue against the idea that all this complexity is directly encoded in the DNA of organisms. Instead, the organism must encode only the simpler rules of engagement (rules like: 1. smell a pheromone? 2. Dropt the dung) and that the complexity results as "order for fee" through the naturally occurring emergent property of nonlinear systems.

Later chapters describe life as being an emergent property on the edge of chaos. There is lots of interesting information here, relating to evolutionary biology and describing how "the edge of chaos" facilitates evolution, and can result in wildly unpredictable outcomes. This part of the book also has worrisome implications for public policy. For example, here in Oregon, the Federal administration recently decided that too much analysis was going into wildlife management. So they decided to cut through the red tape, ignore biologists, and limit water flows in the Lower Klamath drainage basin.

Sole and Goodwin would argue that complex biological systems are very complex, and that their response to sudden changes in conditions can result in wildly unpredictable outcomes. We saw that here in Oregon, recently, as tens of thousands of fish died. Biologists attribute this disaster to parasites that live naturally in the water at all times. However, the lowered flows, and higher temperatures, in the river stressed the fish and pushed them closer together. The weakened fish were subsequently more prone to infection, and the closer proximity facilitated dispersal of the disease. The population reached a subsequent threshold where an epidemic ensued, killing a significant fraction of the fish, and putting people's lives in turmoil who depended on the fish for their livelihoods.

This example illustrates the problems and dangers inherent in managing wildlife populations. Though bearcats may yearn for simple solutions, these systems are, in fact, complex. Simplistic thinking and/or the inability to engage in sophisticated modeling and prediction can result in disasters. This is as true for the Klamath River basin as it is for Earth's climate and the likely effects of widespread pollution from gases that trap heat near the earth, and raise the global temperature.

This is not an easy book to read. It has many equations, and much of the mathematics is non-trivial and involves concepts from nonlinear systems that many readers may not be familiar with. Other terminology in the book is equally aimed at people who already have some exposure to the science at hand. I hope that does not dissuade you. Often, the mathematical details can be skipped (though you will miss some of the most interesting stuff that way). And a dictionary can help you with unfamiliar terminology. Just be aware that this book will demand more of your intellectual capacity than the typical science book that's been written for the arm-chair scientists. But I think it's worth it. I certainly enjoyed it.

Advanced introduction to complex systems
This is a very interesting book. Athough there is some available literature on the recent advances in complex systems, it is often too general for the readers interested in having a good picture of how the area is developed and what type of (really) new advances are taking place. I think that this book, together with some literature on chaos (particularly Ian Stewart's book "Does God Play Dice?") and self-organization (I would strongly recomend Coveney's book "The Arrow of Time") provides a very useful guide to some of the most interesting findings, particularly within biological sciences. Although the most recent breakthroughs in complex networks are not there (not surprisingly) and the range of topics is certainly broad, I think the authors did a pretty good job in presenting a well-defined picture of the importance of emergence and phase transitions in genetics, ecology, evolution and brain dynamics (to cite just a few). You might agree with their views or not, but I think their enthusiam is contagious and makes you seriouly consider these ideas. The boxes, even if not allways self-contained (more references in the final list would have been helpful) trigger further interest in knowing more about the underlying maths and physics. Given the limitations imposed by a popular science book, I think they did a good job. This book should be a must-read for everyone interested in complex systems but also to those who feel that the analytic (so called reductionist) view of reality needs to be complemented with a wider perspective. I am myself molecular biologist, and in spite of the success of my own field over the last decades, I think it's time for some fresh air. Both approaches are needed and this book can give you a first glimpse of why the two approaches are required. I enjoyed reading it and loved the final paragraph. ... Read more

Book Description

This book provides a complete stand alone coverage with which someone conversant with computers could build and analyse the output from a discrete event simulation model. The implementation of models concentrates on the use of general purpose procedure oriented languages, as opposed to special purpose simulation languages, and on the use of C in particular. By concentrating on a widely available language and providing the source code of a simulation library on disk, simulation is made accessible and cost effective in both a teaching and industrial context. ... Read more

Reviews (1)

very good book on simple and practical simulation
Some comparisons with similar in scope book by Myron McDougall are requiried, as Myron's book seems to be much more popular.

Watkins gives very solid yet accessible treatment of all standard simulation areas:methodology, programming implementation issues, random numbers, entitiesand resources, scheduling, queues, gathering results, data analysis, basicstatistical knowledge required, experimental design - and some case studies[ethernet one of them].

The treatment level is eminently suitable forundergrads, similar to McDougall's book.

The package in standard ANSI Cthat comes with this book is much better in functionality than smpl. Thereis more functionality in entities, queues, scheduling, better random numberimplementation.

The lower popularity of Watkins' book is probably causedby the title - no 'computer' in the title (unlike McDougall). It may bealso caused by slightly narrower scope - concentrating more on theprogramming side of simulation than giving slighly broader overview of thetopic.

Still, it's a pity that this book didn't get more popular. ... Read more

Book Description

This new edition accommodates recent advances in GPS technology and considers its full operational capability. Updated or new information has been included although the overall structure conforms to the former editions. The textbook explains in comprehensive manner the concepts of GPS as well as the latest applications in surveying, navigation, and attitude determination. Special emphasis is put on the mitigation of Selective Availability effects by applying differential techniques (DGPS) or by using precise orbit and satellite clock information from various services. Description of project planning, observation, and data processing is provided for novice GPS users. ... Read more

Reviews (2)

A resource for more than just GPS
This is an excellent book for anyone that works with spacecraft geometry and/or timekeeping. It contains concise descriptions of coordinate systems, orbital elements and timekeeping. I've been using it as an algorithm 'cookbook'. This is not a book for a casual GPS user, or someone who is sqeamish about math. It's much easier to use than the Astronomical Almanac for basic algorithms. Like a fool, I lent it out. Now I need to buy another one.

More theory than practice!
As a commercial GPS user, I was looking for a book that would offer a fairly basic overview of GPS, but that would still go into significant detail. This book does exactly that, but it also covers a lot of the mathematical theory behind GPS. This book certainly isn't introductory and I think would be more suited to a surveyor with a good knowledge of surveying techniques who was interested in GPS. The mathematics gets a bit heavy for a non-mathematician but Chapter 7 (Surveying with GPS) is an excellent introduction/review of the practical uses of GPS in the field. A good intermediate-advanced level book, probably very suited to students. ... Read more

Book Description

IEEE Press Series in Biomedical Engineering
Metin Akay, Series Editor

A valuable synthesis of system theory and real-world applications for biomedical instrumentation.

System theory is becoming increasingly important to medical applications. Yet, biomedical and digital signal processing researchers rarely have expertise in practical medical applications, and medical instrumentation designers usually are unfamiliar with system theory. System Theory and Practical Applications for Biomedical Signals bridges those gaps in a practical manner, showing how various aspects of system theory are put into practice by industry.

The chapters are intentionally organized in groups of two chapters, withthe first chapter describing a system theory technology, and the second chapter describing an industrial application of this technology. Each theory chapter contains a general overview of a system theory technology, which is intended as background material for the application chapter. Each application chapter contains a history of a highlighted medical instrument, summary of appropriate physiology, discussion of the problem of interest and previous empirical solutions, and review of a solution that utilizes the theory in the previous chapter.

Written from the perspective of an industry insider who actually made useful products based on the theory, this pragmatic guide combines traditional DSP and compartmental modeling, as well as pairing in-depth discussions of practical medical instrumentation applications and system t