Nonlinear Time Series Analysis [Paperback]

New edition of a successful advanced text on nonlinear time series analysis.The time variability of many natural and social phenomena is not well described by standard methods of data analysis. Nonlinear time series analysis uses chaos theory and nonlinear dynamics to understand such seemingly unpredictable behaviour. Results are applied to real data from physics, biology, medicine, and engineering. While based on a sound mathematical background, the book emphasises practical usefulness. Researchers from all experimental disciplines, including physics, the life sciences, and economy, will find guidance for the analysis of real world systems.The time variability of many natural and social phenomena is not well described by standard methods of data analysis. Nonlinear time series analysis uses chaos theory and nonlinear dynamics to understand such seemingly unpredictable behaviour. Results are applied to real data from physics, biology, medicine, and engineering. While based on a sound mathematical background, the book emphasises practical usefulness. Researchers from all experimental disciplines, including physics, the life sciences, and economy, will find guidance for the analysis of real world systems.The time variability of many natural and social phenomena is not well described by standard methods of data analysis. However, nonlinear time series analysis uses chaos theory and nonlinear dynamics to understand seemingly unpredictable behavior. The results are applied to real data from physics, biology, medicine, and engineering in this volume. Researchers from all experimental disciplines, including physics, the life sciences, and the economy, will find the work helpful in the analysis of real world systems. First Edition Hb (1997): 0-521-55144-7 First Edition Pb (1997): 0-521-65387-8Preface; Acknowledgements; Part I. Basic Topics: 1. Introduction: why nonlinear methods?; 2. Linear tools and general considerations; 3. Phase space methods; 4. Determinism and prló+