Multiscale Analysis of Complex Time Series (Hardcover)

Yinhe Cao

ISBN 10: 0471654701 / ISBN 13: 9780471654704

Published by John Wiley & Sons Inc, New York, 2007

About this Item

Hardcover. The only integrative approach to chaos and random fractal theory Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Multiscale Analysis of Complex Time Series fills this pressing need by presenting chaos and random fractal theory in a unified manner. Adopting a data-driven approach, the book covers: DNA sequence analysisEEG analysisHeart rate variability analysisNeural information processingNetwork traffic modelingEconomic time series analysisAnd more Additionally, the book illustrates almost every concept presented through applications and a dedicated Web site is available with source codes written in various languages, including Java, Fortran, C, and MATLAB, together with some simulated and experimental data. The only modern treatment of signal processing with chaos and random fractals unified, this is an essential book for researchers and graduate students in electrical engineering, computer science, bioengineering, and many other fields. Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471654704

Bibliographic Details

Title: Multiscale Analysis of Complex Time Series (...

Publisher: John Wiley & Sons Inc, New York

Publication Date: 2007

Binding: Hardcover

Condition: new

Edition: 1st Edition

About this title

Synopsis:

The only integrative approach to chaos and random fractal theory Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Multiscale Analysis of Complex Time Series fills this pressing need by presenting chaos and random fractal theory in a unified manner. Adopting a data-driven approach, the book covers:* DNA sequence analysis* EEG analysis* Heart rate variability analysis* Neural information processing* Network traffic modeling* Economic time series analysis* And more Additionally, the book illustrates almost every concept presented through applications and a dedicated Web site is available with source codes written in various languages, including Java, Fortran, C, and MATLAB, together with some simulated and experimental data. The only modern treatment of signal processing with chaos and random fractals unified, this is an essential book for researchers and graduate students in electrical engineering, computer science, bioengineering, and many other fields.

About the Author:

Jianbo Gao is an Assistant Professor of the Department of Electrical and Computer Engineering at the University of Florida. Yinhe Cao is the CEO of BioSieve. Wen-wen Tung is an Assistant Professor of the Department of Earth and Atmospheric Sciences at Purdue University, West Lafayette, Indiana. Jing Hu is a Research Engineer of the Department of Electrical and Computer Engineering at the University of Florida.