Pattern Recognition and String Matching (Combinatorial Optimization, 13)

The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes students and professionals in computer science, mathematics, statistics, and electrical engineering. We wish to thank all the authors for their valuable efforts, which made this book a reality. Thanks also go to all reviewers who gave generously of their time and expertise. Front Matter....Pages i-viii Correcting the Training Data....Pages 1-41 Context Free Grammars and Semantic Networks for Flexible Assembly Recognition....Pages 43-72 Stochastic Recognition of Occluded Objects....Pages 73-103 Approximate String Matching for Angular String Elements with Applications to On-line and Off-line Handwriting Recognition....Pages 105-130 Uniform, Fast Convergence of Arbitrarily Tight Upper and Lower Bounds on the Bayes Error....Pages 131-134 Building RBF Networks for Time Series Classification by Boosting....Pages 135-153 Similarity Measures and Clustering of String Patterns....Pages 155-193 Pattern Recognition for Intrusion Detection in Computer Networks....Pages 195-218 Model-Based Pattern Recognition....Pages 219-254 Structural Pattern Recognition in Graphs....Pages 255-279 Deriving Pseudo-Probabilities of Correctness Given Scores (DPPS)....Pages 281-294 Weighed Mean Generalized Median of Strings....Pages 295-314 A Region-Based Algorithm for Classifier-Independent Feature Selection....Pages 315-340 Inference of K-Piecewise Testable Tree Languages....Pages 341-351 Mining Partially Periodic Patterns With Unknown Periods From Event Stream....Pages 353-377 Combination of Classifiers for Supervised Learning: A Survey....Pages 379-410 Image Segmentation and Pattern Recognition: A Novel Concept, the Histogram of Connected Elements....Pages 411-463 Prototype Extraction for k -NN Classifiers using Median Strings....Pages 465-476 Cyclic String Matching: Efficient Exact and Approximate Algorithms....Pages 477-497 Homogeneity, Autocorrelation and Anisotropy in Patterns....Pages 499-516 Robust Structural Indexing through Quasi-Invariant Shape Signatures and Feature Generation....Pages 517-544 Energy Minimisation Methods for Static and Dynamic Curve Matching....Pages 545-563 Recent Feature Selection Methods in Statistical Pattern Recognition....Pages 565-615 Fast Image Segmentation under Noise....Pages 617-646 Set Analysis of Coincident Errors and Its Applications for Combining Classifiers....Pages 647-671 Enhanced Neighbourhood Specifications for Pattern Classification....Pages 673-702 Algorithmic Synthesis in Neural Network Training for Pattern Recognition....Pages 703-739 Binary Strings and multiclass learning problems....Pages 741-763 This volume is the most comprehensive one in its field. It is a collection of 28 state-of-the-art articles contributed by experts of pattern recognition, string matching, or both. It contains fundamental concepts and notations, as well as reports on current research with respect to both methodology and applications. In particular, it includes string matching related techniques for structural pattern recognition. It also explores many applications of pattern recognition strategies to image segmentation, intrusion detection, handwriting recognition and others. This book is a good reference tool for scientists who depend on problems in pattern recognition and string matching. Target readers include researchers in computer science, statistics, mathematics, and electrical Engineering, as well as students. It is suitable for both specialists and uninformed readers