Once the input values are given, the active rules in a fuzzy inference execution have been determined. Based on the observation, our approach is to identify the active rules before fuzzy inference execution. To achieve this goal, our architecture provides the following two mechanisms: (1) a mechanism to ignore the non-active rules before fuzzy inference execution; and (2) a mechanism to arrange the active rules for fuzzy inference execution. The proposed architecture has been implemented using a 0.35μm cell library. Implementation data show that, if the number of active rules is only 4, the inference speed can achieve 23.755 MFLIPS. To the best of our knowledge, our approach is the fastest hardware implementation.
The main concept of type-2 fuzzy logic is that "words mean different things to different people"; thus, there are uncertainties associated with words. Recently, a lot of mathematical theorems have been developed for type-2 fuzzy logic. However, to the best of knowledge, there has been no hardware implementation. In this paper, we propose the first hardware architecture to support the type-2 fuzzy inference execution. Moreover, we also use a 0.35μm cell library to implement the proposed architecture. Implementation data show that the inference speed reaches up to 3.125 MFLIPS with 2 inputs, 1 output and 64 rules.
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