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E-raamat: Digital Pattern Recognition

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  • Formaat: PDF+DRM
  • Sari: Communication and Cybernetics 10
  • Ilmumisaeg: 07-Mar-2013
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642677403
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Digital Pattern RecognitionSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Communication and Cybernetics 10
  • Ilmumisaeg: 07-Mar-2013
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642677403
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Since its publication in 1976, the original volume has been warmly received. We have decided to put out this updated paperback edition so that the book can be more accessible to students. This paperback edition is essentially the same as the original hardcover volume except for the addition of a new chapter (Chapter 7) which reviews the recent advances in pattern recognition and image processing. Because of the limitations of length, we can only report the highlights and point the readers to the literature. A few typographical errors in the original edition were corrected. We are grateful to the National Science Foundation and the Office of Naval Research for supporting the editing of this book as well as the work described in Chapter 4 and a part of Chapter 7. West Lafayette, Indiana March 1980 K. S. Fu Preface to the First Edition During the past fifteen years there has been a considerable growth of interest in problems of pattern recognition. Contributions to the blossom of this area have come from many disciplines, including statistics, psychology, linguistics, computer science, biology, taxonomy, switching theory, communication theory, control theory, and operations research. Many different approaches have been proposed and a number of books have been published. Most books published so far deal with the decision-theoretic (or statistical) approach or the syntactic (or linguistic) is still far from its maturity, many approach.

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1. Introduction.- 1.1 What is Pattern Recognition?.- 1.2 Approaches to
Pattern Recognition.- 1.3 Basic Non-Parametric Decision Theoretic
Classification Methods.- 1.4 Training in Linear Classifiers.- 1.5 Bayes
(Parametric) Classification.- 1.6 Sequential Decision Model for Pattern
Classification.- 1.7 Bibliographical Remarks.- References.-
2. Topics in
Statistical Pattern Recognition.- 2.1 Nonparametric Discrimination.- 2.2
Learning with Finite Memory.- 2.3 Two-Dimensional Patterns and Their
Complexity.- References.-
3. Clustering Analysis.- 3.1 Introduction.- 3.2 The
Initial Description.- 3.3 Properties of a Cluster, a Clustering Operator and
a Clustering Process.- 3.4 The Main Clustering Algorithms.- 3.5 The Dynamic
Clusters Method.- 3.6 Adaptive Distances in Clustering.- 3.7 Conclusion and
Future Prospects.- References.-
4. Syntactic (Linguistic) Pattern
Recognition..- 4.1 Syntactic (Structural) Approach to Pattern Recognition.-
4.2 Linguistic Pattern Recognition System.- 4.3 Selection of Pattern
Primitives.- 4.4 Pattern Grammar.- 4.5 High-Dimensional Pattern Grammars.-
4.6 Syntax Analysis as Recognition Procedure.- 4.7 Concluding Remarks.-
References.-
5. Picture Recognition.- 5.1 Introduction.- 5.2 Properties of
Regions.- 5.3 Detection of Objects.- 5.4 Properties of Detected Objects.- 5.5
Object Extraction.- 5.6 Properties of Extracted Objects.- 5.7 Representation
of Objects and Pictures.- References.-
6. Speech Recognition and
Understanding..- 6.1 Principles of Speech, Recognition, and Understanding.-
6.2 Recent Developments in Automatic Speech Recognition.- 6.3 Speech
Understanding.- 6.4 Assessment of the Future.- References.-
7. Recent
Developments in Digital Pattern Recognition..- 7.1 A General Viewpoint of
Pattern Recognition.- 7.2 Tree Grammars forSyntactic Pattern Recognition.-
7.3 Syntactic Pattern Recognition Using Stochastic Languages.- 7.4
Error-Correcting Parsing.- 7.5 Clustering Analysis for Syntactic Patterns.-
7.6 Picture Recognition.- 7.7 Speech Recognition and Understanding.-
References.
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