Sequential methods in pattern recognition and machine learning [[electronic resource] /] / K.S. Fu

• Record Nr.: UNINA9910778600003321
• Autore: Fu K. S (King Sun), <1930-1985.>
• Pubbl/distr/stampa: New York, : Academic Press, 1968
• ISBN: 1-282-29019-3; 9786612290190; 0-08-095559-2
• Descrizione fisica: 1 online resource (245 p.)
• Collana: Mathematics in science and engineering ; ; v. 52
• Disciplina: 001.5/3
• Soggetti: Perceptrons; Statistical decision; Machine learning
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Front Cover; Sequential Methods in Pattern Recognition and Machine Learning; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1.1 Pattern Recognition; 1.2 Deterministic Classification Techniques; 1.3 Training in Linear Classifiers; 1.4 Statistical Classification Techniques; 1.5 Sequential Decision Model for Pattern Classification; 1.6 Learning in Sequential Pattern Recognition Systems; 1.7 Summary and Further Remarks; References; Chapter 2. Feature Selection and Feature Ordering; 2.1 Feature Selection and Ordering-Information Theoretic Approach; 2.2 Feature Selection and Ordering-Karhunen-Loève Expansion2.3 Illustrative Examples; 2.4 Summary and Further Remarks; References; Chapter 3. Forward Procedure for Finite Sequential Classification Using Modified Sequential Probability Ratio Test; 3.1 Introduction; 3.2 Modified Sequential Probability Ratio Test-Discrete Case; 3.3 Modified Sequential Probability Ratio Test-Continuous Case; 3.4 Procedure of Modified Generalized Sequential Probability Ratio Test; 3.5 Experiments in Pattern Classification; 3.6 Summary and Further Remarks; References; Chapter 4. Backward Procedure for Finite Sequential Recognition Using Dynamic Programming4.1 Introduction; 4.2 Mathematical Formulation ; and Basic Functional Equation; 4.3 Reduction of Dimensionality; 4.4 Experiments in Pattern Classification; 4.5 Backward Procedure for Both Feature Ordering and Pattern Classification; 4.6 Experiments in Feature Ordering and Pattern Classification; 4.7 Use of Dynamic Programming for Feature-Subset Selection; 4.8 Suboptimal Sequential Pattern Recognition; 4.9 Summary and Further Remarks; References; Chapter 5. Nonparametric Procedure in Sequential Pattern Classification5.1 Introduction; 5.2 Sequential Ranks and Sequential Ranking Procedure; 5.3 A Sequential Two-Sample Test Problem; 5.4 Nonparametric Design of Sequential Pattern Classifiers; 5.5 Analysis of Optimal Performance and a Multiclass Generalization; 5.6 Experimental Results and Discussions; 5.7 Summary and Further Remarks; References; Chapter 6. Bayesian Learning in Sequential Pattern Recognition Systems; 6.1 Supervised Learning Using Bayesian Estimation Techniques; 6.2 Nonsupervised Learning Using Bayesian Estimation Techniques; 6.3 Bayesian Learning of Slowly Varying Patterns6.4 Learning of Parameters Using an Empirical Bayes Approach; 6.5 A General Model for Bayesian Learning Systems; 6.6 Summary and Further Remarks; References; Chapter 7. Learning in Sequential Recognition Systems Using Stochastic Approximation; 7.1 Supervised Learning Using Stochastic Approximation; 7.2 Nonsupervised Learning Using Stochastic Approximation; 7.3 A General Formulation of Nonsupervised Learning Systems Using Stochastic Approximation; 7.4 Learning of Slowly Time-Varying Parameters Using Dynamic Stochastic Approximation; 7.5 Summary and Further Remarks
• Sommario/riassunto: Sequential methods in pattern recognition and machine learning