Decision, estimation, and classification: an introduction to pattern recognition and related topics

Probability theory for random vectors simple statistical decision procedures operations upon random vectors feature extraction and nonlinear mapping quadratic and linear classifiers parameter estimation nonparametric estimation and classification estimating and bounding the probability of error classification of stationary time series context-dependent methods other methods of classification.