A PARAMETERIZED FUZZY PROCESSOR AND ITS APPLICATIONS

In this paper, a parameterized fuzzy processor (PFP) is presented base d on a designed fuzzy instruction set of the parameterized fuzzy numbe r (PFN). This PFN is presented by some parameters of the universe of t he discourse instead of a series of the membership grades. The algorit hms of these instructions are based on the parameter operations to imp lement the fuzzy arithmetics and the fuzzy reasoning methods. The inst ruction set supports the versatility of the fuzzy information, e.g., f uzzy arithmetic operations, inference operations, fuzzy logic operatio ns, data translations and data exchangements. Based upon these, the ch aracteristics of the PFN are discussed, and the architecture of the PF P outlined is constructed in this paper and its processing time is sav ed due to the adaptation of the parameterized fuzzy number (PFN). To e valuate the performance of PFN instructions and PFP structure, two exp eriments are presented. One is the speed performance evaluated for the PFN to compare with the discrete fuzzy number (DFN). The other is the confirmation of the feasibility and the capability of the instruction s, which is demonstrated by three examples related to human inference, intuitive control and decision-making.