Description: Nonlinear Dynamical Systems : Feedforward Neural Network Perspectives, Hardcover by Sandberg, I. W. (EDT); Lo, James T.; Fancourt, Craig L.; Principe, Jose C.; Katagiri, Shigeru; Haykin, Simon, ISBN 0471349119, ISBN-13 9780471349112, Brand New, Free P&P in the UK The first truly up-to-date look at the theory and capabilities of nonlinear dynamical systems that take the form of feedforward neural network structures
Considered one of the most important types of structures in the study of neural networks and neural-like networks, feedforward networks incorporating dynamical elements have important properties and are of use in many applications. Specializing in experiential knowledge, a neural network stores and expands its knowledge base via strikingly human routes-through a learning process and information storage involving interconnection strengths known as synaptic weights.
In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six leading authorities describe recent contributions to the development of an analytical basis for the understanding and use of nonlinear dynamical systems of the feedforward type, especially in the areas of control, signal processing, and time series analysis. Moving from an introductory discussion of the different aspects of feedforward neural networks, th then addresses:
* Classification problems and the related problem of approximating dynamic nonlinear input-output maps
* The development of robust controllers and filters
* The capability of neural networks to approximate functions and dynamic systems with respect to risk-sensitive error
* Segmenting a time series
It then sheds light on the application of feedforward neural networks to speech processing, summarizing speech-related techniques, and reviewing feedforward neural networks from the viewpoint of fundamental design issues. An up-to-date and authoritative look at the ever-widening technical boundaries and influence of neural networks in dynamical systems, this volume is an indispensable resource for researchers in neural networks and a reference staple for libraries.
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Book Title: Nonlinear Dynamical Systems : Feedforward Neural Network Perspect
Number of Pages: 312 Pages
Publication Name: Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives
Language: English
Publisher: John Wiley & Sons INC International Concepts
Item Height: 240 mm
Subject: Computer Science
Publication Year: 2001
Type: Textbook
Item Weight: 696 g
Subject Area: Mechanical Engineering
Author: Jose C. Principe, Craig L. Fancourt, Simon Haykin, Shigeru Katagiri, James T. Lo, Irwin W. Sandberg
Item Width: 176 mm
Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
Format: Hardcover
