Pattern Recognition Using Neural Networks

• Part I FUNDAMENTALS OF PATTERN RECOGNITION ; 0. Basic Concepts of Pattern Recognition ; 1. Decision Theoretic Algorithms ; 2. Structural Pattern Recognition ; Part II INTRODUCTORY NEURAL NETWORKS ; 3. Artificial Neural Network Structures ; 4. Supervised Training via Error Backpropogation: Derivations ; 5. Acceleration and Stabilization of Supervised Gradient Training of MLPs ; Part III ADVANCED FUNDAMENTALS OF NEURAL NETWORKS ; 6. Supervised Training via Strategic Search ; 7. Advances in Network Algorithms for Recognition ; 8. Using Hopfield Recurrent Neural Networks ; Part IV NEURAL, FEATURE, AND DATA ENGINEERING ; 9. Neural Engineering and Testing of FANNs ; 10. Feature and Data Engineering

This is a fairly comprehensive introduction to feedforward neutral networks...the book is accessible and would be well-suited to serve as a text for its intended audience Short Book Review Vol. 17 No. 3 '... makes its subject easy to understand by offering intuitive explanations and examples... lives up to its claim as a practical neural network text and will be an excellent resource for those who want to implement neural networks, rather than just learn the theory.' Scientific Computing World, September 1997