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For m > 2, whether the optimal property is still valid remains to be justified. However, the classification procedure is close to optimal in 41 STATISTICAL PATTERN RECOGNITION that the average number of feature measurements required to reject a pattern class from consideration is nearly minimum when two hypotheses (the hypothesis of a pattern class to be rejected and the hypothesis of a class not rejected) are considered. A general block diagram for a sequential recognition system is shown in Fig.

With the transducer, the loss of information may be unintentional, while with the feature extractor and the classifier, the loss of information is quite intentional. T h e feature extractor is expected to preserve only the information needed for classification, and the classifier preserves only the classification itself. From an abstract point of view, this division of the problem into representation, feature extraction, and classification is arbitrary. T h e entire process can be viewed as a single mapping from object space to decision space.

These mappings are almost always many-to-one, with some information usually being lost at each step. With the transducer, the loss of information may be unintentional, while with the feature extractor and the classifier, the loss of information is quite intentional. T h e feature extractor is expected to preserve only the information needed for classification, and the classifier preserves only the classification itself. From an abstract point of view, this division of the problem into representation, feature extraction, and classification is arbitrary.

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