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Textbook
Pattern Recognition: Statistical, Structural and Neural ApproachesISBN: 978-0-471-52974-3
Paperback
384 pages
September 1991, ©1992
 This is a Print-on-Demand title. It will be printed specifically to fill your order. Please allow an additional 10-15 days delivery time. The book is not returnable.
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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.
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.
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Special Topics
Resources for
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