Fractals and Chaos Simplified for the Life Sciences
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Product details:
- Publisher OUP USA
- Date of Publication 5 February 1998
- ISBN 9780195120240
- Binding Paperback
- No. of pages288 pages
- Size 279x215x14 mm
- Weight 659 g
- Language English
- Illustrations line figures throughout 0
Categories
Short description:
There is a growing interest on the part of undergraduate and graduate students and investigators in applying fractals and chaos (nonlinear dynamics) to a variety of problems in biology and medicine. This book explains fractals and chaos and illustrates their use with examples from biomedical research. The author presents the material in a unique style that doesn't require a strong background in mathematics. The ideas are presented in a straightforward way without
technical jargon. One concept at a time is explained in a set of facing pages, with text on the left page and graphics on the right page. The graphics pages can be copied directly on to transparencies for teaching.
Long description:
Fractals and chaos are currently generating excitement across various scientific and medical disciplines. Biomedical investigators, graduate students, and undergraduates are becoming increasingly interested in applying fractals and chaos (nonlinear dynamics) to a variety of problems in biology and medicine. This accessible text lucidly explains these concepts and illustrates their uses with examples from biomedical research. The author presents the material in a
unique, straightforward manner which avoids technical jargon and does not assume a strong background in mathematics. The text uses a step-by-step approach by explaining one concept at a time in a set of facing pages, with text on the left page and graphics on the right page; the graphics pages can be
copied directly onto transparencies for teaching. Ideal for courses in biostatistics, fractals, mathematical modelling of biological systems, and related courses in medicine, biology, and applied mathematics, Fractals and Chaos Simplified for the Life Sciences will also serve as a useful resource for scientists in biomedicine, physics, chemistry, and engineering.
The book is very well produced, with excellent diagrams and very informative notes provided beside the main text. It also provides an extensive list of references for further reading.
Table of Contents:
Part I Fractals
Introduction
Self-Similarity
Scaling
Dimension
Statistical Properties
Summary
Part II Chaos
Introduction
Sensitivity to Initial Conditions
Bifurcations
Analyzing Data
Control of Chaos
Summary
Part III Other Methods
The Big Picture
