Type-2 Fuzzy System Software Development and Implementation

Type-2 fuzzy logic systems extend traditional fuzzy sets by introducing secondary membership functions to handle higher-order uncertainties. This implementation covers key algorithms for type-2 fuzzy inference systems, including interval type-2 fuzzy set operations, type reduction techniques like Karnik-Mendel (KM) algorithm, and defuzzification methods. The code structure demonstrates practical applications in time-varying channel equalization and uncertainty modeling.