Fuzzy inference systems with no any rule base and linearly parameter growth

作     者：ShitongWANC KorrisF.L.CHUNG JiepingLU BinHAN DewenHU 

作者机构：DepartmentofComputerSchoolofInformationSouthernYangtseUniversityWuxiJiangsu214036China DeparmentofComputingHongKongPolytechnicUniversityHongKongChina DepartmentofComputerSoutheastUniversityNanjingJiangsu210016China DepartrmentofComputerEastChinaShipbuildingInstituteZhenjiangJiangsu212003China SchoolofAutomationNationalDefenseUniversityofScience＆TechnologyChangshaHunan410073China 

出 版 物：《控制理论与应用（英文版）》 (控制理论与技术(英文版))

年 卷 期：2004年第2卷第2期

页      面：185-192页

学科分类：08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 080201[工学-机械制造及其自动化] 

基　　金：This work was supported by the RGC Competitive Earmarked Research Grant (No. PolyU 5065/98E) Natural Science Foundation of China (No. 60225015) Natural Science Foundation of Jiangsu Province (No. BK2003017) National Key Labruary of Novel Software Tech 

主　　题：Fuzzy inference Fuzzy systems Universal approximation Computational complexity Linearly parameter growth 

摘      要：A class of new fuzzy inference systems New-FISs is *** with the standard fuzzy system, New-FIS is still a universal approximator and has no fuzzy rule base and linearly parameter growth. Thus, it effectively overcomes the second curse of dimensionality:there is an exponential growth in the number of parameters of a fuzzy system as the number of input variables,resulting in surprisingly reduced computational complexity and being especially suitable for applications,where the complexity is of the first importance with respect to the approximation accuracy.