scispace - formally typeset
Open AccessBook

Chaos Theory Tamed

Reads0
Chats0
TLDR
Chaos Theory Tamed as mentioned in this paper provides a toolkit for readers, including vectors, phase space, Fourier analysis, time-series analysis, and autocorrelation, to learn and use the vocabulary of chaos.
Abstract
What is this business called 'chaos'? What does it deal with? Why do people think it's important? And how did the term 'chaos' - long associated with disorder - come to signify a new paradigm in the orderly realm of mathematics? The concept of chaos is one of the most exciting and rapidly expanding research topics of recent decades. Chaos might underlie many kinds of well-known processes - the performance of the stock market, the weather, the cries of newborn babies, the dripping of a leaky faucet, and more.In "Chaos Theory Tamed", scientist Garnett P. Williams walks the reader through this exciting territory, building an understanding of chaos and its significance in our lives. "Chaos" is a mathematical subject. If you seek bodice-ripping romance, this book is not for you. But if you are a researcher working with data...a scientist, engineer, or economist who has specialized outside the field of mathematics...or an interested person with a bit of background in algebra and statistics...then "Chaos Theory Tamed" can help you understand the basic concepts of this relatively new arm of science.Williams explains the terms necessary for an understanding of chaos theory. He discusses 'sensitive dependence on initial conditions' and what that means for long-term predictions. He explores the role of the chaotic or 'strange' attractor, order within chaos, fractal structure, and the emerging concepts of self-organization and complexity. Drawing from mathematics, physics, and statistics, the book provides a toolkit for readers, including vectors, phase space, Fourier analysis, time-series analysis, and autocorrelation.Williams describes routes that systems may take from regular behavior to chaos - period doubling, intermittency, and quasiperiodicity - and discusses nonlinear equations that can give rise to chaos. Dimension is a basic ingredient of chaos, and Williams brings clarity to the many ways in which this term is used by specialists in the field. And he explains how the magnitude of chaos may be gauged by Lyapunov exponents, Kolmogorov-Sinai entropy, and mutual information - mysterious terms that 'aren't all that difficult once we pick them apart,' says Williams. "Chaos Theory Tamed" makes generous use of lists, graphs, field examples, summaries, and - perhaps most important - friendly language to help the reader learn and use the vocabulary of chaos. It will help scientists, students, and others outside mathematics to use the concepts of chaos in working with data, and it will give the interested lay reader a foothold on the fundamentals of this new realm of thought.

read more

Citations
More filters
Journal ArticleDOI

Statistics and Data Analysis in Geology

Book

Regular and Chaotic Dynamics

TL;DR: In this article, a self consistent treatment of the subject at the graduate level and as a reference for scientists already working in the field is presented. But the focus is on the mechanics for generating chaotic motion, methods of calculating the transitions from regular to chaotic motion and the dynamical and statistical properties of the dynamics when it is chaotic.
Book ChapterDOI

Multivariate Density Estimation

TL;DR: Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariateData and the comparative lack of parametric models to represent it.
Journal ArticleDOI

A Wavelet-Chaos Methodology for Analysis of EEGs and EEG Subbands to Detect Seizure and Epilepsy

TL;DR: It is observed that while there may not be significant differences in the values of the parameters obtained from the original EEG, differences may be identified when the parameters are employed in conjunction with specific EEG subbands.
Journal ArticleDOI

Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective*

TL;DR: This article proposes that the SCM research community adopt such a dynamic and systems-level orientation that brings to the fore the adaptivity of firms and the complexity of their interrelations that are often inherent in supply networks.
References
More filters
Journal ArticleDOI

Deterministic nonperiodic flow

TL;DR: In this paper, it was shown that nonperiodic solutions are ordinarily unstable with respect to small modifications, so that slightly differing initial states can evolve into considerably different states, and systems with bounded solutions are shown to possess bounded numerical solutions.
Journal ArticleDOI

Determining Lyapunov exponents from a time series

TL;DR: In this article, the authors present the first algorithms that allow the estimation of non-negative Lyapunov exponents from an experimental time series, which provide a qualitative and quantitative characterization of dynamical behavior.
Journal Article

Spectral Analysis and Time Series

TL;DR: In this article, the authors introduce the concept of Stationary Random Processes and Spectral Analysis in the Time Domain and Frequency Domain, and present an analysis of Processes with Mixed Spectra.
Related Papers (5)