Understanding Nonlinear Dynamics | 
 enlarge | Authors: Daniel Kaplan, Leon Glass
Publisher: Springer
Category: Book
List Price: $69.95
Buy New: $49.64
You Save: $20.31 (29%)
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Rating:  3 reviews
Sales Rank: 647495
Media: Paperback
Pages: 440
Number Of Items: 1
Shipping Weight (lbs): 1.4
Dimensions (in): 9.1 x 6.1 x 1
ISBN: 0387944400
Dewey Decimal Number: 515.352
EAN: 9780387944401
Publication Date: December 19, 1997
Availability: Usually ships in 1-2 business days
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Product Description
UNDERSTANDING NONLINEAR DYNAMICS is based on an undergraduate course taught for many years to students in the biological sciences. The text provides a clear and accessible development of many concepts from contemporary dynamics, including stability and multistability, cellular automata and excitable media, fractals, cycles, and chaos. A chapter on time-series analysis builds on this foundation to provide an introduction to techniques for extracting information about dynamics from data. The text will be useful for courses offered in the life sciences or other applied science programs, or as a supplement to emphasize the application of subjects presented in mathematics or physics courses. Extensive examples are derived from the experimental literature, and numerous exercise sets can be used in teaching basic mathematical concepts and their applications. Concrete applications of the mathematics are illustrated in such areas as biochemistry, neurophysiology, cardiology, and ecology. The text also provides an entry point for researchers not familiar with mathematics but interested in applications of nonlinear dynamics to the life sciences.
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| Customer Reviews:
 Simply an Iluminating path to Understand Nonlinear Dynamics February 13, 1998
17 out of 19 found this review helpful
It happens that in any field there is a book that iluminates. This is the one in Nonlinear Dynamics. With it's clear and simple but mathematically and conceptually rich presentation this text opens the mind towards the mathemathics that you learn in your two first University years, as aplicated to innumerable Life Science examples, but at the same time interesting for any other field's applications (Physics, Maths, Chemists,..). This book deals with Dynamics in a Superb Way. Contents: 1-Finite Difference Equations. 2-Boolean Networks and Celular Automata. 3-Self Similarity and Fractal Geometry. 4-One Dimensional Differential Equations. 5-Two Dimensional Differential Equations. 6-Time Series Analysis. Apendix-A: A Multifunctional Appendix. Appendix-B: A Note on Computer Notation. Buy it, you might learn how much you can do with you mathematics knowledge!
Gentle introduction to nonlinear dynamics July 24, 2001
Steve Uhlig (Delft, The Netherlands)
10 out of 11 found this review helpful
This is a gentle introdution to nonlinear dynamics, maths are well explained, illustrations are abundant, the overview is very good overall, even if subjects are only touched. It could also serve as an introduction to finite-difference and differential equations for non-maths students.Undergrads looking for something smooth on nonlinear dynamics should get this one...but for advanced readers it is probably a waste of time.
 A good introduction to the mechanical side... May 30, 2002
Yuri Kuzyk (Toronto, Ontario Canada)
11 out of 12 found this review helpful
It is funny that there is so much hype about Wolfram's "A New Kind of Science" when this book neatly pointed out his big 'discoveries' back in 1995. That is, all of Wolfram's opus can be found in chapter 2 of this book.The book provides a good (and relatively gentle) introduction to the mechanistic view of non-linear dynamics. Many different applications of non-linear dynamics, from physics to biology, are overviewed and many detailed examples are provided. In all, this is a great reference. The only shortcomings are the lack of discussions about frameworks, particularly mechanistic systems, and how they influence the applicability of the models. That is, some understanding of systems theory (von Bertalanffy in particular and the work of cybernetics as well) should have been included to point out the fact that the linear causality implied by many models immediately limits their applicability.
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