Pattern Classification

Pattern Classification, 2nd Edition, is a comprehensive textbook on the mathematical and computational principles of pattern recognition. Building upon the 1973 first edition, which became an established reference in the field, this volume provides foundational guidance to help readers choose appropriate classification techniques for given classes of problems.

The presentation introduces core theoretical frameworks across statistical pattern recognition, neural networks, and machine learning theory. In addition to parametric and nonparametric decision methods, the text addresses the theory of invariances alongside algorithm-independent evaluation techniques.

Recommended as both an instructional text for students and a reference for practicing professionals, the volume integrates worked examples to support practical study and analysis.