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OverviewThis monograph explores the close relationship of various well-known pattern recognition problems that have so far been considered independent. These relationships became apparent with the discovery of formal procedures for addressing known problems and their generalisations. The generalised problem formulations were analysed mathematically and unified algorithms were found. The main scientific contribution of this book is the unification of two main streams in pattern recognition - the statistical one and the structural one. The material is presented in the form of ten lectures, each of which concludes with a discussion with a student. It provides new views and numerous original results in their field. Written in an easily accessible style, it introduces the basic building blocks of pattern recognition, demonstrates the beauty and the pitfalls of scientific research, and encourages good habits in reading mathematical text. Full Product DetailsAuthor: M.I. Schlesinger , Václav HlavácPublisher: Springer Imprint: Springer Edition: Softcover reprint of the original 1st ed. 2002 Volume: 24 Dimensions: Width: 15.50cm , Height: 2.80cm , Length: 23.50cm Weight: 0.831kg ISBN: 9789048160273ISBN 10: 9048160278 Pages: 522 Publication Date: 22 September 2011 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Out of stock  The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsLecture 1 Bayesian statistical decision making.- Lecture 2 Non-Bayesian statistical decision making.- Lecture 3 Two statistical models of the recognised object.- Lecture 4 Learning in pattern recognition.- Lecture 5 Linear discriminant function.- Lecture 6 Unsupervised learning.- Lecture 7 Mutual relationship of statistical and structural recognition.- Lecture 8 Recognition of Markovian sequences.- Lecture 9 Regular languages and corresponding pattern recognition tasks.- Lecture 10 Context-free languages, their 2-D generalisation, related tasks.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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