Parallel processing of fuzzy inferences

Rule based systems are computationally very demanding, since a large number of rules has to be evaluated every time new input data are observed in order to undertake a corresponding action. The authors study the possible improvements in performance by using parallel processing. Both fine grade algorithms and standard multiprocessor architectures for Mamdani-type fuzzy systems with two inputs and one output are considered. It is shown, that a speed-up close to linear may be achieved. The results may be extended to systems with more than two inputs.<>