Multiscale Analysis of Complex Time Series (PDF)
Integration of Chaos and Random Fractal Theory, and Beyond
(Sprache: Englisch)
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...
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...
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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.
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.
Autoren-Porträt von Jianbo Gao, Yinhe Cao, Wen-Wen Tung, Jing Hu
Jianbo Gao is an Assistant Professor of the Department ofElectrical 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.
Bibliographische Angaben
- Autoren: Jianbo Gao , Yinhe Cao , Wen-Wen Tung , Jing Hu
- 2008, 1. Auflage, 368 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 0470191643
- ISBN-13: 9780470191644
- Erscheinungsdatum: 12.07.2008
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Grösse: 15 MB
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Sprache:
Englisch
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