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SCALABLE ARCHITECTURE FOR HIGH-SPEED MULTIDIMENSIONAL FUZZY INFERENCE SYSTEMS
2011
Journal of Circuits, Systems and Computers
This paper presents a scalable architecture suitable for the implementation of high-speed fuzzy inference systems on reconfigurable hardware. The main features of the proposed architecture, based on the Takagi-Sugeno inference model, are scalability, high performance, and flexibility. A scalable Fuzzy Inference System (FIS) must be efficient and practical when applied to complex situations, such as multidimensional problems with a large number of membership functions and a large rule base.
doi:10.1142/s0218126611007359
fatcat:5xcs5lscbfbshjhowix7fzosme