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The Nonlinear Workbook: Chaos, Fractals, Cellular Automata, Genetic Algorithms, Gene Expression Programming, Support Vector Machine, Wavele
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The Nonlinear Workbook provides a comprehensive treatment of all the techniques in nonlinear dynamics together with C++, Java and SymbolicC++ implementations. The book not only covers the theoretical aspects of the topics but also provides the practical tools. To understand the material, more than 100 worked out examples and 150 ready to run programs are included. New topics added to the fifth edition are Langton's ant, chaotic data communication, self-controlling feedback, differential forms and optimization, T-norms and T-conorms with applications.
- Published on: 2011-03-16
- Released on: 2011-03-16
- Original language: English
- Dimensions: 9.21" h x 1.45" w x 6.30" l,
- Binding: Paperback
- 642 pages
Review
"This handbook provides a large selection of topics related to iteration of nonlinear maps, from a practical and computational point of view. The great diversity of topics is supported by more than 100 worked examples and 150 programs." -- Zentralblatt MATH
From the Inside Flap
The Nonlinear Workbook provides a comprehensive treatment of all the techniques in nonlinear dynamics together with C++, Java and SymbolicC++ implementations. The book not only covers the theoretical aspects of the topics but also provides the practical tools. To understand the material, more than 100 worked out examples and 150 ready to run programs are included. New topics added to the fifth edition are Langton's ant, chaotic data communication, self-controlling feedback, differential forms and optimization, T-norms and T-conorms with applications.
Most helpful customer reviews
10 of 10 people found the following review helpful.
Astonishing Overview But Very Advanced-- Dynamic Systems is the Missing Keyword
By Let's Compare Options Preptorial
The "South African" trim size of this text is unusual at 6 x 9 x 1.5 (inches), so the hefty 620 pages makes for a compact but heavy package, of GREAT value! For context, I'm CTO of a calculus animation company, and we use a lot of the techniques in this manual in our daily programming, design and Engineering work, including teaching chips to learn math.
The authors keep using the words "we are keeping this simple, for beginners" when describing their (mostly C++ with some Java) code, but South African "beginners" must already have MIT Masters in Math, Engineering and Computer Science if that's the case! The volume is so PACKED with great information on these unusual topics that there really is little time or space for beginners, to be honest. For example, (p. 309), we're exploring Karush-Kuhn-Tucker conditions for optimization, and with little warning, in two pages, we jump into and out of linear programming, then partial derivatives.
Math has become so specialized that it is EXTREMELY RARE to find even advanced Engineers and Mathematicians that have as broad a background as this collection requires. That's also its value-- even if you're very good in only a couple areas (say, linear algebra and inequalities), you can look up what get's tough and use this as a foundation. This is NOT for self study, but rather as a reference and adjunct with help from other volumes that cover the many topics in more detail. I'm not sure how I'd structure a course around it, other than an outstanding "applied" introduction to nonlinear techniques for grad students.
For teachers, you might find the "tempo" of this text a little foreign, but interesting, and PACKED with example after example. The tempo is bang-bang-bang-see? The examples are given staccato one after another, then the authors take a breather to do a little explaining. As an example, the authors give a frequent example of fixed points in dynamical systems as f(x)=x using 4x(1-x) as an example. You pause, look at it, then solve the quadratic yourself for 0 and 3/4 roots. These are just given, then 13 pages later, an example of the quadratic steps (that you already did yourself) is then given!
What's not in the title, subject, keywords, intro, covers, etc. is the actual topic of the book: Dynamic Systems Modeling. There are many dynamic systems books out there, but this is the ONLY one we've found that covers such a broad range of topics with a lot of OOP code that works quite well. I'm guessing that the 4 previous editions helped work out kinks in the code, because very few of these fail to compile first time. Like some old Engineers that use C++ but only use the "C" pieces and not the OOP parts (data/setter-getter/methods), there is enough here even if you don't use a lot of OOP. But if you do, there also is plenty of Java to keep you happy. Some of the C++ reads like pseudo-code and is "symbolic C++" to give you the general idea of the algorithm's implementation rather than exact code. BUT there are HUNDREDS of worked out examples that do run flawlessly.
The applied nature of the coverage is the real value here. The authors do take the time to discuss how many of these models are practically applied TODAY. Finding a book rather than a journal article that does this is very rare. And the journals that do cover these topics only come out a few times a year and cost $400+ US for a subscription!
I can't really say this is for beginners, but right in the middle of a bunch of complex code and math, the authors suddenly get very basic and explain stuff at an undergrad level. Fun, curious, and rewarding, but still too complex for self study in my opinion, unless you have a tutor or are good at supplementing with other texts and tutorials. On the other hand, as a survey and practical reference to the pragmatic sides of fractals, chaos and other "hip" topics-- this is MUCH better than the usual "consumer" fare of a lot of speculation with no substance. This text/manual/handbook has substance in every sentence.
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