{"title":"Membership function generator based on bit-shift operation for self-organizing relationship (SOR) network","authors":"Hakaru Tamukoh, Keiichi Horio, Takeshi Yamakawa","doi":"10.1016/j.ics.2006.12.034","DOIUrl":null,"url":null,"abstract":"<div><p>A 2<sup>−<em>r</em></sup><span> shape of a membership function generator is presented. The proposed membership function generator requires a bit-shifter and a NOR operation only, and thus suits digital hardware implementation well. A fast defuzzification method employing active units is also presented. It reduces a calculation cost for the defuzzification. In this paper, we have successfully applied proposed methods to a self-organizing relationship network. Simulation results show that the proposed method has as good and approximation ability of nonlinear functions as the ordinary method.</span></p></div>","PeriodicalId":84918,"journal":{"name":"International congress series","volume":"1301 ","pages":"Pages 180-183"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ics.2006.12.034","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International congress series","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0531513106006868","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A 2−r shape of a membership function generator is presented. The proposed membership function generator requires a bit-shifter and a NOR operation only, and thus suits digital hardware implementation well. A fast defuzzification method employing active units is also presented. It reduces a calculation cost for the defuzzification. In this paper, we have successfully applied proposed methods to a self-organizing relationship network. Simulation results show that the proposed method has as good and approximation ability of nonlinear functions as the ordinary method.