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Robustness in Statistical Pattern Recognition by Y. Kharin (Paperback, 2010)

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About this product

Product Information

This mograph is devoted to problems of robust (stable) statistical pattern recognition. Experimental data to be classified usually deviate from assumed hypothetical probability models of the data. In such cases traditional decision rules constructed by means of the classical pattern recognition theory based on a fixed hypothetical model of the data often become n-stable, and the classification risk increases n-controllably. The book concentrates on three main problems: robustness evaluation for classical decision rules in the presence of distortion; estimation of critical levels of distortions for given values of the robustness factor; and the construction of robust decision rules with stable classification risk regarding certain types of distortions. Theoretical results are illustrated by computer modelling and by application to medical diagstics. Audience: This volume is primarily intended for mathematicians, statisticians, and engineers in applied mathematics, computer science and cybernetics. It is also recommended as a textbook for a one-semester course for advanced undergraduate and graduate students training in the indicated fields.

Product Identifiers

Brand
Springer
GTIN
9789048147601
UPC
9789048147601
eBay Product ID (ePID)
178293931

Product Key Features

Subject Area
Applied Mathematics
Level
Advanced
Format
Paperback
Language
English
Features
Illustrated
Subject
Mathematics
Publication Year
2010
Type
Textbook

Dimensions

Item Height
297 mm
Weight
842g
Depth
17 mm
Height
297mm
Width
210mm
Item Weight
842 g

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