Neural network theory

Author: (Russian) A.N. Galushkin
Publisher:
Publish Date: 2002-12-01
Features: This book discusses the role of neural networks from the perspective of building high-performance computers, providing a detailed analysis of the structural design, learning algorithms, and fault diagnosis of multilayer feedforward networks. The book is divided into four parts:
Part 1 focuses on the various typical structures of feedforward networks;
Part 2 discusses some theoretical issues in neural network learning;
Part 3 studies specific learning algorithms;
Part 4 discusses the reliability and fault diagnosis of neural networks.
The book offers in-depth theoretical analysis and numerous practical examples, with extensive references from Russian scholars in neural network research at the end of each chapter. It serves as a self-study reference for scientists and engineers engaged in neural network research and application, as well as for those working in the field of pattern recognition. It can also be used as a teaching reference for graduate students in related fields. The original book was recommended as a teaching material for senior undergraduate and graduate students in Russia.