The Resource Introduction to statistical pattern recognition, Keinosuke Fukunaga, (electronic resource)

Introduction to statistical pattern recognition, Keinosuke Fukunaga, (electronic resource)

Label
Introduction to statistical pattern recognition
Title
Introduction to statistical pattern recognition
Statement of responsibility
Keinosuke Fukunaga
Creator
Subject
Genre
Language
  • eng
  • eng
Summary
This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapte
Member of
Cataloging source
MiAaPQ
http://library.link/vocab/creatorName
Fukunaga, Keinosuke
Dewey number
  • 006.4
  • 006.4 20
Illustrations
illustrations
Index
index present
Language note
English
LC call number
Q327
LC item number
.F85 1990
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Computer science and scientific computing
http://library.link/vocab/subjectName
  • Pattern perception
  • Decision making
  • Mathematical statistics
Label
Introduction to statistical pattern recognition, Keinosuke Fukunaga, (electronic resource)
Instantiates
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Content category
text
Content type code
txt
Contents
  • Cover; Frontmatter; Half Title Page; Title Page; Copyright; Dedication; Table of Contents; Preface; Acknowledgments; Chapter 1: Introduction; 1.1 Formulation of Pattern Recognition Problems; 1.2 Process of Classifier Design; Notation; References; Chapter 2: Random Vectors and Their Properties; 2.1 Random Vectors and Their Distributions; 2.2 Estimation of Parameters; 2.3 Linear Transformation; 2.4 Various Properties of Eigenvalues and Eigenvectors; Computer Projects; Problems; References; Chapter 3: Hypothesis Testing; 3.1 Hypothesis Tests for Two Classes; 3.2 Other Hypothesis Tests
  • 3.3 Error Probability in Hypothesis Testing3.4 Upper Bounds on the Bayes Error; 3.5 Sequential Hypothesis Testing; Computer Projects; Problems; References; Chapter 4: Parametric Classifiers; 4.1 The Bayes Linear Classifier; 4.2 Linear Classifier Design; 4.3 Quadratic Classifier Design; 4.4 Other Classifiers; Computer Projects; Problems; References; Chapter 5: Parameter Estimation; 5.1 Effect of Sample Size in Estimation; 5.2 Estimation of Classification Errors; 5.3 Holdout, Leave-One-Out, and Resubstitution Methods; 5.4 Bootstrap Methods; Computer Projects; Problems; References
  • Chapter 6: Nonparametric Density Estimation6.1 Parzen Density Estimate; 6.2 k Nearest Neighbor Density Estimate; 6.3 Expansion by Basis Functions; Computer Projects; Problems; References; Chapter 7: Nonparametric Classification and Error Estimation; 7.1 General Discussion; 7.2 Voting kNN Procedure - Asymptotic Analysis; 7.3 Voting kNN Procedure - Finite Sample Analysis; 7.4 Error Estimation; 7.5 Miscellaneous Topics in the kNN Approach; Computer Projects; Problems; References; Chapter 8: Successive Parameter Estimation; 8.1 Successive Adjustment of a Linear Classifier
  • 8.2 Stochastic Approximation8.3 Successive Bayes Estimation; Computer Projects; Problems; References; Chapter 9: Feature Extraction and Linear Mapping for Signal Representation; 9.1 The Discrete Karhunen-Loéve Expansion; 9.2 The Karhunen-Loéve Expansion for Random Processes; 9.3 Estimation of Eigenvalues and Eigenvectors; Computer Projects; Problems; References; Chapter 10: Feature Extraction and Linear Mapping for Classification; 10.1 General Problem Formulation; 10.2 Discriminant Analysis; 10.3 Generalized Criteria; 10.4 Nonparametric Discriminant Analysis
  • 10.5 Sequential Selection of Quadratic Features10.5 Feature Subset Selection; Computer Projects; Problems; References; Chapter 11: Clustering; 11.1 Parametric Clustering; 11.2 Nonparametric Clustering; 11.3 Selection of Representatives; Computer Projects; Problems; References; Backmatter; Appendix A: Derivatives of Matrices; Appendix B: Mathematical Formulas; Appendix C: Normal Error Table; Appendix D: Gamma Function Table; Index; About the Author; Back Cover
Dimensions
unknown
Edition
2nd ed.
Extent
1 online resource (616 p.)
Form of item
online
Isbn
9786611050382
Media category
computer
Media type code
c
Specific material designation
remote
System control number
  • (EBL)294219
  • (OCoLC)476057325
  • (SSID)ssj0000182931
  • (PQKBManifestationID)12001984
  • (PQKBTitleCode)TC0000182931
  • (PQKBWorkID)10173095
  • (PQKB)10292033
  • (MiAaPQ)EBC294219
  • (EXLCZ)991000000000009942
Label
Introduction to statistical pattern recognition, Keinosuke Fukunaga, (electronic resource)
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Content category
text
Content type code
txt
Contents
  • Cover; Frontmatter; Half Title Page; Title Page; Copyright; Dedication; Table of Contents; Preface; Acknowledgments; Chapter 1: Introduction; 1.1 Formulation of Pattern Recognition Problems; 1.2 Process of Classifier Design; Notation; References; Chapter 2: Random Vectors and Their Properties; 2.1 Random Vectors and Their Distributions; 2.2 Estimation of Parameters; 2.3 Linear Transformation; 2.4 Various Properties of Eigenvalues and Eigenvectors; Computer Projects; Problems; References; Chapter 3: Hypothesis Testing; 3.1 Hypothesis Tests for Two Classes; 3.2 Other Hypothesis Tests
  • 3.3 Error Probability in Hypothesis Testing3.4 Upper Bounds on the Bayes Error; 3.5 Sequential Hypothesis Testing; Computer Projects; Problems; References; Chapter 4: Parametric Classifiers; 4.1 The Bayes Linear Classifier; 4.2 Linear Classifier Design; 4.3 Quadratic Classifier Design; 4.4 Other Classifiers; Computer Projects; Problems; References; Chapter 5: Parameter Estimation; 5.1 Effect of Sample Size in Estimation; 5.2 Estimation of Classification Errors; 5.3 Holdout, Leave-One-Out, and Resubstitution Methods; 5.4 Bootstrap Methods; Computer Projects; Problems; References
  • Chapter 6: Nonparametric Density Estimation6.1 Parzen Density Estimate; 6.2 k Nearest Neighbor Density Estimate; 6.3 Expansion by Basis Functions; Computer Projects; Problems; References; Chapter 7: Nonparametric Classification and Error Estimation; 7.1 General Discussion; 7.2 Voting kNN Procedure - Asymptotic Analysis; 7.3 Voting kNN Procedure - Finite Sample Analysis; 7.4 Error Estimation; 7.5 Miscellaneous Topics in the kNN Approach; Computer Projects; Problems; References; Chapter 8: Successive Parameter Estimation; 8.1 Successive Adjustment of a Linear Classifier
  • 8.2 Stochastic Approximation8.3 Successive Bayes Estimation; Computer Projects; Problems; References; Chapter 9: Feature Extraction and Linear Mapping for Signal Representation; 9.1 The Discrete Karhunen-Loéve Expansion; 9.2 The Karhunen-Loéve Expansion for Random Processes; 9.3 Estimation of Eigenvalues and Eigenvectors; Computer Projects; Problems; References; Chapter 10: Feature Extraction and Linear Mapping for Classification; 10.1 General Problem Formulation; 10.2 Discriminant Analysis; 10.3 Generalized Criteria; 10.4 Nonparametric Discriminant Analysis
  • 10.5 Sequential Selection of Quadratic Features10.5 Feature Subset Selection; Computer Projects; Problems; References; Chapter 11: Clustering; 11.1 Parametric Clustering; 11.2 Nonparametric Clustering; 11.3 Selection of Representatives; Computer Projects; Problems; References; Backmatter; Appendix A: Derivatives of Matrices; Appendix B: Mathematical Formulas; Appendix C: Normal Error Table; Appendix D: Gamma Function Table; Index; About the Author; Back Cover
Dimensions
unknown
Edition
2nd ed.
Extent
1 online resource (616 p.)
Form of item
online
Isbn
9786611050382
Media category
computer
Media type code
c
Specific material designation
remote
System control number
  • (EBL)294219
  • (OCoLC)476057325
  • (SSID)ssj0000182931
  • (PQKBManifestationID)12001984
  • (PQKBTitleCode)TC0000182931
  • (PQKBWorkID)10173095
  • (PQKB)10292033
  • (MiAaPQ)EBC294219
  • (EXLCZ)991000000000009942

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