REAL-TIME FUZZY LOGIC COMPUTATIONS
Brian T. Hemmelman, Chaitanya Chandrana
Abstract
Brian T. Hemmelman, Chaitanya Chandrana
Abstract
Traditionally digital systems and electronics have been based on Boolean algebra and binary numbers. It is, however, possible to utilize fuzzy set theory in digital applications, especially for control applications in consumer electronics and other real-time systems. Fuzzy logic has been used effectively to handle nonlinear systems. In order to accelerate the operation of fuzzy logic systems we have developed hardware chips that allow direct computation and manipulation of fuzzy set membership functions, fuzzy set operators, fuzzification, fuzzy associative matrices, and center of area defuzzification. Unlike software implementations of fuzzy set theory, the computational architecture we have designed allows all fuzzy logic computations to be performed completely in parallel and in real-time.
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Traditionally digital systems and electronics have been based on Boolean algebra and binary numbers. It is, however, possible to utilize fuzzy set theory in digital applications, especially for control applications in consumer electronics and other real-time systems. Fuzzy logic has been used effectively to handle nonlinear systems. In order to accelerate the operation of fuzzy logic systems we have developed hardware chips that allow direct computation and manipulation of fuzzy set membership functions, fuzzy set operators, fuzzification, fuzzy associative matrices, and center of area defuzzification. Unlike software implementations of fuzzy set theory, the computational architecture we have designed allows all fuzzy logic computations to be performed completely in parallel and in real-time.
Key concepts: Defuzzification, Fuzzy electronics, Fuzzy set operations, Fuzzy logic, Fuzzy classification, Fuzzy number, Fuzzy associative matrix, Neuro-fuzzy