Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches (Signals and Communication Technology)
| Author | : | |
| Rating | : | 4.66 (550 Votes) |
| Asin | : | 0387263284 |
| Format Type | : | paperback |
| Number of Pages | : | 232 Pages |
| Publish Date | : | 2015-01-17 |
| Language | : | English |
DESCRIPTION:
The book focuses on the Volterra and Wiener models for nonlinear systems … . From the reviews: "In this book, the author presents simple, concise, easy-to-understand methods for identifying nonlinear systems using adaptive filter algorithms well known for linear systems identification. It is another contribution to the current literature on the subject. Stavrakakis, Zentralblatt MATH, Vol. The book will be useful for graduate students, engineers and researchers in the area of the nonlinear systems identification and adaptive signal processing." (George S. 1130 (8), 2008)
Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.. Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes
"Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches" according to Ifiok J. Umoh. The book titled "Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches" by Tokunbo Ogunfunmi is a very good introductory book to the area of Adaptive Signal Processing in general with a focus on nonlinear adaptive signal processing.The author begins by reviewing a lot of the fundamental ideas in linear systems theory that have been extended to the area of nonlinear systems. This helps the reader to be equipped with the simple DSP fundament. Filling a gap! The book has a direct-to-the-point approach where the author addresses orthogonal and non-orthogonal polynomial modeling methods to nonlinear systems.The emphasis is given to the Volterra and Wiener models, where the latter issingled out as the most appropriate for adaptive implementation thanks to itsorthogonality properties. At first glance the book looks oversimplified, however, whenreading the details one notices that the book was written in a smat way.I consider