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Applications of Neural Networks

  • Book
  • © 1995

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Table of contents (13 chapters)

  1. Introduction

  2. Supervised Training

    1. Pattern Recognition and Classification

    2. Diagnosis and Monitoring

    3. Prediction and Control

    4. Signal Processing

  3. Unsupervised Training

    1. Temporal Sequences — Reinforcement Learning

    2. Mixed- Mode (Supervised and Unsupervised) Training

Keywords

About this book

Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'.
For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.

Editors and Affiliations

  • The University of Edinburgh, UK

    Alan F. Murray

Bibliographic Information

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