Pattern recognition method for reducing classification errors

Data processing: artificial intelligence – Neural network – Learning task

Reexamination Certificate

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C706S015000, C706S025000

Reexamination Certificate

active

07069257

ABSTRACT:
A RBF pattern recognition method for reducing classification errors is provided. An optimum RBF training approach is obtained for reducing an error calculated by an error function. The invention continuously generates the updated differences of parameters in the learning process of recognizing training samples. The modified parameters are employed to stepwise adjust the RBF neural network. The invention can distinguish different degrees of importance and learning contributions among the training samples and evaluate the learning contribution of each training sample for obtaining differences of the parameters of the training samples. When the learning contribution is larger, the updated difference is larger to speed up the learning. Thus, the difference of the parameters is zero when the training samples are classified as the correct pattern type.

REFERENCES:
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patent: 5487133 (1996-01-01), Park et al.
patent: 5675497 (1997-10-01), Petsche et al.
patent: 5701398 (1997-12-01), Glier et al.
patent: 6090044 (2000-07-01), Bishop et al.

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