In: IEEE Transactions on Fuzzy Systems, Special Issue on Hardware, Vol. 4, No. 4, pages 403-417. November 1996.
Abstract: Fuzzy systems implemented in hardware can operate with much higher performance than software implementations on standard microcontrollers. In this paper, three types of fuzzy systems and related hardware architectures are discussed: standard fuzzy controllers, FuNe I fuzzy systems, and fuzzy classifiers based on a neural network structure. Two computer-aided design (CAD) packages for automatic hardware synthesis of standard fuzzy controllers are presented: a hard-wired implementation of a complete fuzzy system on a single or multiple field programmable gate arrays (FPGA) and a modular toolbox called fuzzyCAD for synthesis of reprogrammable fuzzy controllers with architectures due to specified designer constraints. In the fuzzyCAD system, an efficient design methodology has been implemented which covers a large design space in terms of signal representations and component architectures as well as system architectures. Very high-speed integrated-circuits hardware-description language (VHDL) descriptions and usage of powerful synthesis tools allow different technologies to be targeted easily and efficiently. In the last part of this paper, properties and hardware realizations of fuzzy classifiers based on a neural network are introduced. Finally, future perspectives and possible enhancements of the the existing toolkits are outlined.
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