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, ...
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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.
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Add this copy of Nonlinear Time Series Analysis (Cambridge Nonlinear to cart. $195.00, very good condition, Sold by Sequitur Books rated 5.0 out of 5 stars, ships from Boonsboro, MD, UNITED STATES, published 1997 by Cambridge University Press.
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Seller's Description:
Very Good. Size: 7x1x10; Hardcover and dust jacket. Good binding and cover. Shelf wear. Printer's error with some corners enlarged and folded over. Jacket sunned. Clean, unmarked pages. xvi, 304 pages: illustrations; 26 cm. "Deterministic chaos offers a striking explanation for irregular behavior and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. This book provides experimentalists with methods for processing, enhancing, and analyzing measured signals using these methods, and for theorists it also demonstrates the practical applicability of mathematical results."-Cambridge University Press.