Abstract
This paper presents a general and model-independent analysis of the problem of feature extraction in pattern recognition. Two criteria are derived which ensure the existence of a complete feature space. This is a space which contains exactly the information relevant for the classification process following feature extraction. Several possibilities for the construction of such a complete feature space are discussed and experimental results which indicate the potential of the proposed methods for practical applications are presented. >
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