From engineering to statistics, from computer science to the social sciences, 'Statistical Pattern Recognition' shows how closely these fields are related in terms of application. Areas such as database design, artificial neural networks and decision support are common to all. The author also examines the more diverse theoretical topics available to the practitioner or researcher, such as outlier detection and model selection, and concludes each section with a description of the wider range of practical applications and the future developments of theoretical techniques. Providing an introduction to statistical pattern theory and techniques that draws on material from a wide range of fields, 'Statistical Pattern Recognition' is a must for all technical professionals wanting to get up to speed on the recent advances in this dymanic subject area.

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