Approximation Capability of SISO SBR Fuzzy Systems based on Fuzzy Implications

The term approximate reasoning (AR) refers to methods and methodologies that enable reasoning with imprecise inputs to obtain meaningful outputs. AR schemes involving fuzzy sets are one of the best known applications of fuzzy logic in the wider sense. Fuzzy Inference Systems (FIS) have many degrees of freedom, viz., the underlying fuzzy partition of the input and output spaces, the fuzzy logic operations employed, the fuzzification and defuzzification mechanism used, etc. This freedom gives rise to a variety of FIS with differing capabilities. One of the important factors considered while employing an FIS is its approximation capability. Many studies have appeared on this topic and due to space constraints, we only refer the readers to the following exceptional review on this topic [10] and the references therein.