Neural Networks For Intelligent Signal Processing
Author:   Anthony Zaknich (The Univ Of Western Australia, Australia)
Publisher:   World Scientific Publishing Co Pte Ltd
Volume:   4
ISBN:  

9789812383051


Pages:   508
Publication Date:   24 January 2003
Format:   Hardback
Availability:   In Print   Availability explained
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Neural Networks For Intelligent Signal Processing


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Overview

This title provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing. It has been tested on students, unfamiliar with neural networks, who were able to pick up enough details to successfully complete their masters or final year undergraduate projects. The text also presents a comprehensive treatment of a class of neural networks called common bandwidth spherical basis function NNs, including the probabilistic NN, the modified probabilistic NN, and the general regression NN.

Full Product Details

Author:   Anthony Zaknich (The Univ Of Western Australia, Australia)
Publisher:   World Scientific Publishing Co Pte Ltd
Imprint:   World Scientific Publishing Co Pte Ltd
Volume:   4
Dimensions:   Width: 15.20cm , Height: 24.10cm , Length: 23.00cm
Weight:   0.830kg
ISBN:  

9789812383051


ISBN 10:   9812383050
Pages:   508
Publication Date:   24 January 2003
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

A Brief Historical Overview; Basic Concepts; ANN Performance Evaluation; Basic Pattern Recognition Principles; ADALINES, Adaptive Filters, and Multi-Layer Perceptrons; Probabilistic Neural Network Classifier; General Regression Neural Network; The Modified Probabilistic Neural Network; Advanced MPNN Developments; Neural Networks Similar to the Common Bandwidth Spherical Basis Function Regression ANNs; Unsupervised Learning Neural Networks; Other Neural Network Models; Statistical Learning Theory; Application to Intelligent Signal Processing; Application to Intelligent Control.

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