Pattern Recognition: Statistical, Structural and Neural Approaches (Paperback)

STATISTICAL PATTERN RECOGNITION (StatPR).

Supervised Learning (Training) Using Parametric and Nonparametric Approaches.

Linear Discriminant Functions and the Discrete and Binary Feature Cases.

Unsupervised Learning and Clustering.

SYNTACTIC PATTERN RECOGNITION (SyntPR).

Overview.

Syntactic Recognition via Parsing and Other Grammars.

Graphical Approaches to SyntPR.

Learning via Grammatical Inference.

NEURAL PATTERN RECOGNITION (NeurPR).

Introduction to Neural Networks.

Introduction to Neural Pattern Associators and Matrix Approaches.

Feedforward Networks and Training by Backpropagation.

Content Addressable Memory Approaches and Unsupervised Learning in NeurPR.

Appendices.

References.

Permission Source Notes.

Index.