完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Chen, Cheng-Hung | en_US |
dc.contributor.author | Lin, Cheng-Jian | en_US |
dc.contributor.author | Lin, Chin-Teng | en_US |
dc.date.accessioned | 2014-12-08T15:15:51Z | - |
dc.date.available | 2014-12-08T15:15:51Z | - |
dc.date.issued | 2007 | en_US |
dc.identifier.isbn | 978-1-4244-0707-1 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/11834 | - |
dc.identifier.uri | http://dx.doi.org/10.1109/CIISP.2007.369205 | en_US |
dc.description.abstract | In this paper, a recurrent functional-link-based neural fuzzy system (RFLNFS) is proposed for prediction of time sequence and skin color detection. The proposed RFLNFS model uses functional link neural network as the consequent part of fuzzy rules. The RFLNFS model can generate the consequent part of a nonlinear combination of the input variables. The recurrent network is embedded in the RFLNFS by adding feedback connections in the second layer, where the feedback units act as memory elements. An online learning algorithm, which consists of structure learning and parameter learning, is also presented. Finally, the RFLNFS is applied to two simulations. The simulation results of the dynamic system modeling have shown that the RFLNFS model can solve the temporal problem and the RFLNFS model has superior performance than other models. | en_US |
dc.language.iso | en_US | en_US |
dc.title | A recurrent functional-link-based neural fuzzy system and its applications | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.doi | 10.1109/CIISP.2007.369205 | en_US |
dc.identifier.journal | 2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN IMAGE AND SIGNAL PROCESSING | en_US |
dc.citation.spage | 415 | en_US |
dc.citation.epage | 420 | en_US |
dc.contributor.department | 電控工程研究所 | zh_TW |
dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
dc.identifier.wosnumber | WOS:000252299800071 | - |
顯示於類別: | 會議論文 |