Jianbo Gao, Yinhe Cao, Wen-Wen Tung, Jing Hu

Multiscale Analysis of Complex Time Series (eBook, PDF)

Integration of Chaos and Random Fractal Theory, and Beyond

• Format: PDF

Produktbeschreibung

The only integrative approach to chaos and random fractaltheory Chaos and random fractal theory are two of the most importanttheories developed for data analysis. Until now, there has been nosingle book that encompasses all of the basic concepts necessaryfor researchers to fully understand the ever-expanding literatureand apply novel methods to effectively solve their signalprocessing problems. Multiscale Analysis of Complex TimeSeries fills this pressing need by presenting chaos and randomfractal 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 conceptpresented through applications and a dedicated Web site isavailable with source codes written in various languages, includingJava, Fortran, C, and MATLAB, together with some simulated andexperimental data. The only modern treatment of signal processingwith chaos and random fractals unified, this is an essential bookfor researchers and graduate students in electrical engineering,computer science, bioengineering, and many other fields.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, D ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 368
• Erscheinungstermin: 12. Juli 2008
• Englisch
• ISBN-13: 9780470191644
• Artikelnr.: 37291512

Autorenporträt

Jianbo Gao is an Assistant Professor of the Department ofElectrical and Computer Engineering at the University ofFlorida. Yinhe Cao is the CEO of BioSieve. Wen-wen Tung is an Assistant Professor of the Department ofEarth and Atmospheric Sciences at Purdue University, WestLafayette, Indiana. Jing Hu is a Research Engineer of the Department of Electricaland Computer Engineering at the University of Florida.

Inhaltsangabe

Preface.1. Introduction.2. Overview of fractal and chaos theory.3. Basics of probability theory and stochastic processes.transform, and probability generating function.4. Fourier analysis and wavelet multiresolution analysis.5. Basics of fractal geometry.6. Self-similar stochastic processes.7. Stable laws and Levy motions.8. Long memory processes and structure-function-based multifractal analysis.9. Multiplicative multifractals.10. Stage-dependent multiplicative processes.11. Models of power-law-type behavior.12. Bifurcation theory.13. Chaotic time series analysis.14. Power-law sensitivity to initial conditions (PSIC).15. Multiscale analysis by the scale-dependent Lyapunov exponent (SDLE).Appendix A: Description of data.Appendix B: Principal Component Analysis (PCA), Singular Value. Decomposition (SVD), and Karhunen-Loève (KL) expansion.Appendix C: Complexity measures.References.Index.