一个硬件模糊推理系统的设计与实现

Donald L. Hung, William F. Zajak
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引用次数: 12

摘要

本文讨论了基于广义样项推理规则、“迷你”模糊蕴涵函数、“最大-最小”模糊构成规则和重心去模糊化方法的专用硬件模糊推理系统的设计。作为一个特例,基于一般设计思想,在单块现场可编程门阵列(FPGA)芯片上实现了一种双输入(前置)、一输出(后置)模糊推理系统,并增加了用于去模糊化的EPROM。包括电路细节和性能数据。还讨论了其他问题,如可扩展性和适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and implementation of a hardware fuzzy inference system

This paper discusses the design of a dedicated hardware fuzzy inference system based on the generalized modus ponens (GMP) inference rule, the “mini” fuzzy implication function, the “max-min” fuzzy composition rule, and the center of gravity (COG) defuzzification method. As a special case, the implementation of a two-input (antecedents), one-output (consequent) fuzzy inference system based on the general design idea was implemented on a single field programmable gate array (FPGA) chip with an extra EPROM for defuzzification. Circuitry details and performance data are included. Additional issues such as extendibility and adaptability are also discussed.

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