发明名称 |
Pattern recognition method for reducing classification errors |
摘要 |
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.
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申请公布号 |
US2004002928(A1) |
申请公布日期 |
2004.01.01 |
申请号 |
US20020279815 |
申请日期 |
2002.10.25 |
申请人 |
INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE |
发明人 |
HUANG YEA-SHUAN |
分类号 |
G06K9/62;G06N3/08;(IPC1-7):G06N3/067;G06E1/00;G06E3/00;G06F15/18;G06G7/00;G06N3/06;G06N3/063 |
主分类号 |
G06K9/62 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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