English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 49378/84106 (59%)
造訪人次 : 7371305      線上人數 : 43
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/95869

    題名: Neural Network-Based Fuzzy Systems
    作者: Su, Mu-Chun;Kao, Chien-Jen;Liu, Kai-Ming
    貢獻者: 淡江大學電機工程學系
    關鍵詞: 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
    日期: 1994-12
    上傳時間: 2014-02-13 11:13:54 (UTC+8)
    摘要: 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.
    關聯: 1994 International Computer Symposium Conference Proceeding Volume 2 of 2,頁1246-1250
    顯示於類別:[電機工程學系暨研究所] 會議論文





    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋