Neural Networks-A Comprehensive Foundation, 2nd Edition by Simon Haykin

Neural Networks-A Comprehensive Foundation, 2nd Edition by Simon S. Haykin

Author: Simon Haykin

Publishers: Prentice Hall International, Inc.

About this Book:

Neural Networks or artificial neural networks to be more precise, represent a technology that is rooted in many disciplines: neuroscience, mathematics, statistics, physics, computer science and engineering.

This book provides a comprehensive foundation of neural networks, recognizing the multidisciplinary  nature of the subject. The material presented in this book is supported with examples. computer-oriented experiments, end-of-chapter problems and a bibliography.


  1. Introduction
  2. Learning Processes
  3. Single Layer Perceptrons
  4. Multilayer Perceptrons
  5. Radial-Basis Function Networks
  6. Support Vector Machines
  7. Committee Machines
  8. Principal Components Analysis
  9. Self-Organizing Maps
  10. Information-Theoretic Models
  11. Stochastic Machines And Their Approximates Rooted In Statistical Mechanics
  12. Neurodynamic Programming
  13. Temporal Processing Using Feedforward Networks
  14. Neurodynamics
  15. Dynamically Driven Recurrent Networks

Download Links (Full Book):

HTTP Download (PDF)


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