Extracting Knowledge From Time Series
An Introduction to Nonlinear Empirical Modeling
Authors: Bezruchko, Boris P., Smirnov, Dmitry A.
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- About this book
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This book addresses the fundamental question of how to construct mathematical models for the evolution of dynamical systems from experimentally-obtained time series. It places emphasis on chaotic signals and nonlinear modeling and discusses different approaches to the forecast of future system evolution. In particular, it teaches readers how to construct difference and differential model equations depending on the amount of a priori information that is available on the system in addition to the experimental data sets. This book will benefit graduate students and researchers from all natural sciences who seek a self-contained and thorough introduction to this subject.
- Reviews
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From the reviews:
“Extracting knowledge from time series is a very neat title–it exactly encapsulates the topic which the authors hope to cover in this volume. … This is admirable, and the result is valuable. … This is overall a useful volume for providing an overview of the area … .” (Michael Small, Mathematical Reviews, Issue 2012 d)
“Another book on time-series! … it is a textbook for physicists and practitioners, and in this way of thought it is welcome. Its main purpose is to explain and illustrate how time series can be used to construct mathematical models for dynamical systems. … step by step the applications supports the presentation of the basic theoretical formulation.” (Guy Jumarie, Zentralblatt MATH, Vol. 1210, 2011)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Extracting Knowledge From Time Series
- Book Subtitle
- An Introduction to Nonlinear Empirical Modeling
- Authors
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- Boris P. Bezruchko
- Dmitry A. Smirnov
- Series Title
- Springer Series in Synergetics
- Copyright
- 2010
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- eBook ISBN
- 978-3-642-12601-7
- DOI
- 10.1007/978-3-642-12601-7
- Hardcover ISBN
- 978-3-642-12600-0
- Softcover ISBN
- 978-3-642-26482-5
- Series ISSN
- 0172-7389
- Edition Number
- 1
- Number of Pages
- XXII, 410
- Number of Illustrations
- 162 b/w illustrations
- Topics
