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Sequential methods in pattern recognition and machine learning /
Sequential methods in pattern recognition and machine learning.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Academic Press,
1968.
|
| Colección: | Mathematics in science and engineering ;
v. 52. |
| Temas: | |
| Acceso en línea: | Texto completo Texto completo Texto completo |
MARC
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| 100 | 1 | |a Fu, K. S. |q (King Sun), |d 1930-1985. | |
| 245 | 1 | 0 | |a Sequential methods in pattern recognition and machine learning / |c K.S. Fu. |
| 260 | |a New York : |b Academic Press, |c 1968. | ||
| 300 | |a 1 online resource (xi, 227 pages) | ||
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| 490 | 1 | |a Mathematics in science and engineering ; |v v. 52 | |
| 504 | |a Includes bibliographical references and indexes. | ||
| 588 | 0 | |a Print version record. | |
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2010. |5 MiAaHDL | ||
| 538 | |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |u http://purl.oclc.org/DLF/benchrepro0212 |5 MiAaHDL | ||
| 583 | 1 | |a digitized |c 2010 |h HathiTrust Digital Library |l committed to preserve |2 pda |5 MiAaHDL | |
| 520 | |a Sequential methods in pattern recognition and machine learning. | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 2.2 Feature Selection and Ordering-Karhunen-Lo�eve 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
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| 776 | 0 | 8 | |i Print version: |a Fu, K.S. (King Sun), 1930- |t Sequential methods in pattern recognition and machine learning. |d New York : Academic Press, 1968 |z 9780122695506 |w (DLC) 68008424 |w (OCoLC)435344 |
| 830 | 0 | |a Mathematics in science and engineering ; |v v. 52. | |
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