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1999 PB Nonlinear Time Series Analysis (Cambridge Nonlinear Science Series, Se..
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N.º de artículo de eBay:297776749367
Características del artículo
- Estado
- En muy buen estado
- Notas del vendedor
- “Pages are crisp and clean, no marking. Cover is verygood. Binding is tight/good.”
- ISBN
- 9780521653879
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Product Identifiers
Publisher
Cambridge University Press
ISBN-10
0521653878
ISBN-13
9780521653879
eBay Product ID (ePID)
1024970
Product Key Features
Number of Pages
320 Pages
Language
English
Publication Name
Nonlinear Time Series Analysis
Publication Year
1999
Subject
Mechanics / Fluids, Linear & Nonlinear Programming, Probability & Statistics / Time Series, Mathematical Analysis
Type
Textbook
Subject Area
Mathematics, Science
Series
Cambridge Nonlinear Science Ser.
Format
Trade Paperback
Dimensions
Item Height
0.7 in
Item Weight
23.7 Oz
Item Length
9.7 in
Item Width
6.9 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
96-037159
Dewey Edition
21
Series Volume Number
Series Number 7
Illustrated
Yes
Dewey Decimal
519.5/5
Table Of Content
Part I. Basic Concepts: 1. Introduction: why nonlinear methods?; 2. Linear tools and general considerations; 3. Phase space methods; 4. Determinism and predictability; 5. Instability: Lyapunov exponents; 6. Self-similarity: dimensions; 7. Using nonlinear methods when determinism is weak; 8. Selected nonlinear phenomena; Part II. Advanced Topics: 9. Advanced embedding methods; 10. Chaotic data and noise; 11. More about invariant quantities; 12. Modeling and forecasting; 13. Chaos control; 14. Other selected topics; Appendix 1. Efficient neighbour searching; Appendix 2. Program listings; Appendix 3. Description of the experimental data sets.
Synopsis
Deterministic chaos provides a novel framework for the analysis of irregular time series. Traditionally, nonperiodic signals are modeled by linear stochastic processes. But even very simple chaotic dynamical systems can exhibit strongly irregular time evolution without random inputs. Chaos theory offers completely new concepts and algorithms for time series analysis which can lead to a thorough understanding of the signal. The book introduces a broad choice of such concepts and methods, including phase space embeddings, nonlinear prediction and noise reduction, Lyapunov exponents, dimensions and entropies, as well as statistical tests for nonlinearity. Related topics like chaos control, wavelet analysis and pattern dynamics are also discussed. Applications range from high quality, strictly deterministic laboratory data to short, noisy sequences which typically occur in medicine, biology, geophysics or the social sciences. All material is discussed and illustrated using real experimental data., Deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which seem not to be inherently stochastic. This book describes the most direct link between chaos theory and the real world, which is the analysis of time series from real systems in terms of nonlinear dynamics.
LC Classification Number
QA280 .K355 1997
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