The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in

which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in

practice. More recently, neural network techniques and methods imported statistical learning theory have been receiving

increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes,

sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection

of training and test samples, and performance evaluation.-The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in

which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in

practice. More recently, neural network techniques and methods imported　statistical learning theory have been receiving

increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes,

sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection

of training and test samples, and performance evaluation.