Using credit assignment and GBF with dynamic learning rate to enhance the ability of low-dimensional CMAC
碩士 === 大同大學 === 電機工程學系(所) === 92 === Conventional CMAC has a memory size problem at high dimensional input space. Using the neural network structure composed of small CMACs can efficiently solve this problem. By using the advantage of credit assignment and Gaussian basis function, we use it to impro...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2004
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| Online Access: | http://ndltd.ncl.edu.tw/handle/14666150716669599215 |