Neural Network-Based Fuzzy Systems

機構典藏 > College of Engineering > Graduate Institute & Department of Electrical Engineering > Proceeding > Item 987654321/95869

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/95869

Title:	Neural Network-Based Fuzzy Systems
Authors:	Su, Mu-Chun;Kao, Chien-Jen;Liu, Kai-Ming
Contributors:	淡江大學電機工程學系
Keywords:	模糊類神經網路;模糊規則抽取;函數近似;FDHECNNFuzzy Neural Network;Fuzzy Rule Extraction;Function Approximation;Fdhecnn
Date:	1994-12
Issue Date:	2014-02-13 11:13:54 (UTC+8)
Abstract:	In this paper, we discuss how to use FDHECNN's (fuzzy degraded hyperellipsoidal composite neural networks) to extract fuzzy rules for function approximation. The FDHECNN can perform function approximation in the same manner as networks based on Gaussion potential functions, by linear combination of local functions. Furthermore, the output functions of the hidden nodes in the FDHECNN's offer more flexibility than Gaussion potential functions do. A special scheme is developed to find a set of good initial weights in order to speed up the convergence problem. Results of simulations of a system identification demonstrates that the feasibility and robustness of the proposed fuzzy neural networks.
Relation:	1994 International Computer Symposium Conference Proceeding Volume 2 of 2，頁1246-1250
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Proceeding

Files in This Item:

There are no files associated with this item.