Fuzzy JK flip-flops as computational structures: design and implementation

Current research on fuzzy set applications has yielded a better understanding of complex design problems involving nondeterministic human factors. This has in turn resulted in a significant number of efficient software case-study oriented realizations. Concurrently, efficient hardware implementations involving integration of a large number of discrete components have become feasible in light of existing technological achievements. Hirota and Ozawa (1989) introduced the notion of the fuzzy JK flip-flop, considering it an essential and basic component for effective processing of fuzzy information. Continuing with this line of reasoning, a discussion is presented of VLSI implementation issues with emphasis on design platforms to be used with the new structures. Next some comparisons are performed pertaining to the usefulness and realization of several logical connectives, followed by an examination of fuzzy sequential system design. The combinational part of the circuit is embodied in a single layer neural network in which weights are adjusted on the basis of training situations. Numerical considerations highlight the performance of the design process