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Webb
STATISTICAL Copsey
PATTERN
RECOGNITION STATISTICAL
Third Edition
Andrew R. Webb and Keith D. Copsey
Mathematics and Data Analysis Consultancy, Malvern, UK
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.
PATTERN
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, works, support
vector machines, feature selection and feature reduction techniques. Technical descriptions and STATISTICAL
motivations are provided, and the techniques are illustrated using real examples.
Statistical Pattern Recognition, Third Edition:
• Provides a self-contained introduction to statistical pattern recognition. PATTERN
• Includes new material presenting the analysis works. RECOGNITION
• Introduces readers to methods for Bayesian density estimation.
• Presents descriptions of new applications in biometrics, security, finance and
condition monitoring. RECOGNITION
• Provides descriptions and guidance for implementing techniques, which will be
invaluable to software engineers and developers seeking to develop real applications. Third Edition
• Describes mathematically the range of statistical pattern recognition techniques.
• Presents a variety of exercise