UID:
almahu_9947366461802882
Umfang:
1 online resource (309 p.)
ISBN:
1-282-70290-4
,
9786612702907
,
0-08-095621-1
Serie:
Mathematics in science and engineering ; v. 112
Inhalt:
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank
Anmerkung:
Description based upon print version of record.
,
Front Cover; Syntactic Methods in Pattern Recognition; Copyright Page; Contents; Preface; Acknowledgments; Chapter 1 Introduction; 1.1 Syntactic (Structural) Approach to Pattern Recognition; 1.2 Syntactic Pattern Recognition System; 1.3 Preprocessing Techniques; 1.4 Pattern Segmentation; 1.5 Remarks on Syntactic Approach versus Decision-Theoretic Approach; References; Chapter 2 Introduction to Formal Languages; 2.1 Introduction; 2.2 Languages and Phrase-Structure Grammars; 2.3 Finite-State Languages and Finite-State Automata; 2.4 Context-Free Languages and Pushdown Automata
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2.5 Turing Machines and Linear-Bounded Automata2.6 Modified Grammars; References; Chapter 3 Languages for Pattern Description; 3.1 Selection of Pattern Primitives; 3.2 Pattern Grammar: Introduction; 3.3 High Dimensional Pattern Grammars; 3.4 The Use of Semantic Information; References; Chapter 4 Syntax Analysis as a Recognition Procedure; 4.1 Introduction; 4.2 Top-Down Parsing; 4.3 Bottom-Up Parsing; 4.4 LR(k) Grammars; 4.5 An Efficient Top-Down Parser; 4.6 Operator Precedence Grammars; 4.7 Precedence and Extended Precedence Grammars; 4.8 Syntax Analysis of Context-Free Programmed Languages
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ReferencesChapter 5 Stochastic Languages and Stochastic Syntax Analysis; 5.1 Basic Formulations; 5.2 Probability Measures Associated with Linear and Context-Free Grammars; 5.3 Languages Accepted by Stochastic Automata; 5.4 Stochastic Programmed and Indexed Grammars; 5.5 Stochastic Syntax Analysis for Stochastic Context-Free Languages; 5.6 Stochastic Syntax Analysis for Context-Free Programmed Languages; References; Chapter 6 Stochastic Languages for Syntactic Pattern Recognition; 6.1 Stochastic Languages for Pattern Description; 6.2 Estimation of Production Probabilities
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6.3 Examples of Stochastic Syntax AnalysisReferences; Chapter 7 Grammatical Inference for Syntactic Pattern Recognition; 7.1 Introduction and Basic Definitions; 7.2 Grammatical Inference Algorithms by Enumeration; 7.3 Grammatical Inference Algorithms by Induction; 7.4 Bayesian Inference of Stochastic Grammars; 7.5 Synthesis of Stochastic Finite-State Automata; 7.6 A Practical Grammatical Inference System; 7.7 Approximation of Stochastic Languages; References; Appendix A Syntactic Recognition of Chromosome Patterns; Appendix B PDL (Picture Description Language)
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Appendix C Syntactic Recognition of Two-Dimensional Mathematical ExpressionsAppendix D Syntactic Description of Hand-Printed FORTRAN Characters; Appendix E Syntactic Recognition of Chinese Characters; Appendix F Syntactic Recognition of Spoken Words; Appendix G Plex Languages; Appendix H Web Grammars; Appendix I Tree Grammars for Syntactic Pattern Recognition; Author Index; Subject Index
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English
Weitere Ausg.:
ISBN 0-12-269560-7
Sprache:
Englisch
