| 摘要 |
A pattern recognition system capable of handling the non-Gaussian feature vector distribution in the feature vector space such that the recognition rate can be improved while using the pattern matching based on the assumption of the Gaussian feature vector distribution. In the system, a nonlinear transformation for each recognizable category is applied to the feature vector extracted from the input pattern to be recognized, to obtain a transformed feature data for the input pattern, where the nonlinear transformation maps linearly inseparable distributions in a vector space containing the feature vector onto linearly separable distributions. Then, the transformed feature data for the input pattern is compared with reference feature model for each recognizable category indicating a feature vector distribution for each category, to find a category of the input pattern as that of the reference feature model closest to the transformed feature data for the input pattern.
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