Noise Reduction Property of Type-2 Fuzzy Neural Networks
Abstract
In this chapter, an attempt is made to show the effect of input noise in the rule base in a general way. There exist number of papers in literature claiming that the performance of T2FLSs is better than its type-1 counterparts under noisy conditions. We try to justify this claim by simulation studies only for some specific systems. However, in this chapter, such an analysis is done independent of the system to be controlled. For such an analysis, a novel type-2 fuzzy MF (elliptic MF) is proposed. This type-2 MF has certain values on both ends of the support and the kernel, and some uncertain values for other values of the support. The findings of the general analysis ...
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