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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:
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.
Applying COM+ Автор: Gregory Brill Год: 1999 |
Multiscale Analysis of Complex Time Series: Integration of Chaos and Random Fractal Theory, and Beyond Автор: Jianbo Gao, Yinhe Cao, Wen-wen Tung, Jing Hu Год: 2007 |
Strength and Stiffness of Engineering Systems (Mechanical Engineering Series) Автор: Frederick A. Leckie, Dominic J. Dal Bello Год: 2009 |
Physics unified Автор: Harold Aspden Год: 1980 |
Optical sources, detectors, and systems: fundamentals and applications Автор: Robert H. Kingston Год: 1995 |
The Shortcut Guide to Improving Government Services Through Unified Communications Автор: Ken Camp Год: 2010 |