A Neuro-Fuzzy Approach to System Identification
學年 83
學期 1
發表日期 1994-12-15
作品名稱 A Neuro-Fuzzy Approach to System Identification
作品名稱（其他語言）
著者 Su, Mu-Chun; Kao, Chien-Jen
作品所屬單位 淡江大學電機工程學系
出版者
會議名稱 1994 International Symposium on Artificial Neural Networks
會議地點 臺南, 臺灣
摘要 In this paper, we present an innovative approach to the identification of non-linear systems. The proposed neuro-fuzzy system identifier employs a hybrid clustering and least mean squared error (LMS) algorithm. The neuro- fuzzy system under consideration is implemented as an two- layer FHRCNN (fuzzy hyperrectangular composite neural network). The SDDL (supervised decision-directed learning) algorithm is used to find a set of hyperrectangles defined by the parameters of hidden nodes while the LMS algorithm estimates the connection weights from hidden nodes to output nodes. Furthermore, based on the hybrid learning rule, the fuzzy neural networks can evolve automatically to acquire a set of fuzzy if-then rules for approximating the input/output functions of considered systems. A highly nonlinear system is used to test the proposed neural-fuzzy systems. The simulation results demonstrate its feasibility and robustness.
關鍵字 系統識別;類神經網路;模糊理論;System Identification;Neural Network;Fuzzy Theory
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 19941215~19941217
通訊作者
國別 TWN
公開徵稿 Y
出版型式 紙本
出處 Proceedings of 1994 International Symposium on Artificial Neural Networks，頁495-500
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