A prelude to neural networks: adaptive and learning systems

1. Elements of Pattern Recognition. 2. Statistical Pattern Recognition. 3. Algorithms for Pattern Recognition. 4. Applications of Pattern Recognition Technology. 5. Synthesis of Quasi-Optimal Switching Surfaces by Means of Training Techniques. 6. Gradient Identification for Linear Systems.