Fuzzy inference systems with no any base and linearly parameter growth
Shitong WANG
Korris F.L.CHUNG
Jieping LU
Bin HAN
Dewen HU
摘要：A class of new fuzzy inference systems New-FISs is presented. Compared 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.
机标关键词：linearly parameter growthfuzzy systemcomputational complexityfuzzy inference systemsuniversal approximatorapproximation accuracyinput variablesfuzzy rule base
分类号：O1(数学)
资助基金：RGC Competitive Earmarked Research Grant(PolyU 5065/98E)国家自然科学基金(60225015)江苏省自然科学基金(BK2003017)
论文发表日期：2004-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：8( 185-192 )
英文信息