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Pattern Recognition and String Matching [Paperback]

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  • Category: Books (Computers)
  • ISBN-10:  1461379520
  • ISBN-10:  1461379520
  • ISBN-13:  9781461379522
  • ISBN-13:  9781461379522
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  772
  • Pages:  772
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Feb-2011
  • Pub Date:  01-Feb-2011
  • SKU:  1461379520-11-SPRI
  • SKU:  1461379520-11-SPRI
  • Item ID: 100852373
  • List Price: $109.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Oct 16 to Oct 18
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.
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.Correcting the Training Data.- Context Free Grammars and Semantic Networks for Flexible Assembly Recognition.- Stochastic Recognition of Occluded Objects.- Approximate String Matching for Angular String Elements with Applications to On-line and Off-line Handwriting Recognition.- Uniform, Fast Convergence of Arbitrarily Tight Upper and Lower Bounds on the Bayes Error.- Building RBF Networks for Time Series Classification by Boosting.- Similarity Measures and Clustering of String Patterns.- Pattern Recognition for Intrusion Detection in Computer Networks.- Model-Based Pattern Recognition.- Structural Pattern Recognition in Graphs.- Deriving Pseudo-Probabilities of Correctness Given Scores (DPPS).- Weighel&
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