Robert J. Schalkoff is the author of Pattern Recognition: Statistical, Structural and Neural Approaches, published by Wiley.

• STATISTICAL PATTERN RECOGNITION (StatPR). Supervised Learning (Training) Using Parametric and NonparametricApproaches. Linear Discriminant Functions and the Discrete and Binary FeatureCases. 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 MatrixApproaches. Feedforward Networks and Training by Backpropagation. Content Addressable Memory Approaches and Unsupervised Learning inNeurPR. Appendices. References. Permission Source Notes. Index.

Robert J. Schalkoff is the author of Pattern Recognition: Statistical, Structural and Neural Approaches, published by Wiley.

• STATISTICAL PATTERN RECOGNITION (StatPR). Supervised Learning (Training) Using Parametric and NonparametricApproaches. Linear Discriminant Functions and the Discrete and Binary FeatureCases. 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 MatrixApproaches. Feedforward Networks and Training by Backpropagation. Content Addressable Memory Approaches and Unsupervised Learning inNeurPR. Appendices. References. Permission Source Notes. Index.

Robert J. Schalkoff is the author of Pattern Recognition: Statistical, Structural and Neural Approaches, published by Wiley.

• STATISTICAL PATTERN RECOGNITION (StatPR). Supervised Learning (Training) Using Parametric and NonparametricApproaches. Linear Discriminant Functions and the Discrete and Binary FeatureCases. 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 MatrixApproaches. Feedforward Networks and Training by Backpropagation. Content Addressable Memory Approaches and Unsupervised Learning inNeurPR. Appendices. References. Permission Source Notes. Index.