非線(xiàn)性時(shí)間序列分析

內(nèi)容概要

This book provides a thorough review of a class of powerful algorithms for the numerical analysis of complex time series data which were obtained from dynamical systems. These algorithms are based on the concept of state space representations of the underlying dynamics, as introduced by nonlinear dynamics. In particular, current algorithms for state space reconstruction, correlation dimension estimation, testing for determinism and surrogate data testing are presented ?algorithms which have been playing a central role in the investigation of deterministic chaos and related phenomena since 1980. Special emphasis is given to the much-disputed issue whether these algorithms can be successfully employed for the analysis of the human electroencephalogram.

書(shū)籍目錄

ForewordI  Introduction2  Nonlinear Dynamical Systems3  Stochastic Time Series4  A Test for Reversibility5  Detecting Differences between Reconstruction Measures6  Estimating Invariants of Noisy Attractors7  The Correlation Integral of Noisy Attractors8  Spiral Wave Tip Dynamics9  Spatio-temporal Chaos: a Solvable ModelAppendix AAppendix BAppendix CReferencesIndex

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