Page 19 - Introduction to Statistical Pattern Recognition

Chapter I

INTRODUCTION

This book presents and discusses the fundamental mathematical tools for
statistical decision-making processes in pattern recognition. It is felt that the
decision-making processes of a human being are somewhat related to the
recognition of patterns; for example, the next move in a chess game is based
upon the present pattern on the board, and buying or selling stocks is decided
by a complex pattern of information. The goal of pattern recognition is to clar-
ify these complicated mechanisms of decision-making processes and to
automate these functions using computers. However, because of the complex
nature of the problem, most pattern recognition research has been concentrated
on more realistic problems, such as the recognition of Latin characters and the
classification of waveforms. The purpose of this book is to cover the
mathematical models of these practical problems and to provide the fundamen-
tal mathematical tools necessary for solving them. Although many approaches
have been proposed to formulate more complex decision-making processes,
these are outside the scope of this book.

1.1 Formulation of Pattern Recognition Problems

Many important applications of pattern recognition can be characterized
as either waveform classification or classification of geometric figures. For
example, consider the problem of testing a machine for normal or abnormal

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