Statistical Pattern Recognition
Andrew R. Webb
Venduto da Kennys Bookstore, Olney, MD, U.S.A.
Venditore AbeBooks dal 9 ottobre 2009
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Aggiungere al carrelloVenduto da Kennys Bookstore, Olney, MD, U.S.A.
Venditore AbeBooks dal 9 ottobre 2009
Condizione: Nuovo
Quantità: Più di 20 disponibili
Aggiungere al carrelloStatistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Num Pages: 666 pages, black & white illustrations, black & white tables, figures. BIC Classification: PBT; UYQP. Category: (P) Professional & Vocational. Dimension: 242 x 168 x 36. Weight in Grams: 1090. . 2011. 3rd Edition. Paperback. . . . . Books ship from the US and Ireland.
Codice articolo V9780470682289
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques.
This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples.
Statistical Pattern Recognition, 3rd Edition:
The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields.
http://www.wiley.com/go/statistical_pattern_recognition
Dr Andrew Robert Webb, Senior Researcher, QinetiQ Ltd, Malvern, UK.
Dr Keith Derek Copsey, Senior Researcher, QinetiQ Ltd, Malvern, UK.
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