Supervised and Reinforcement Evolution Learning for Recurrent Wavelet Neuro-Fuzzy Networks and Its Applications
碩士 === 朝陽科技大學 === 資訊工程系碩士班 === 93 === In this thesis, supervised and reinforcement evolution learning methods are proposed for recurrent wavelet neuro-fuzzy networks (RWNFN). The RWNFN model is a feedforward multi-layer network which integrates traditional Takagi-Sugeno-Kang (TSK) fuzzy model and th...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2005
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| Online Access: | http://ndltd.ncl.edu.tw/handle/mpf7zx |