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Architectural design of fuzzy inference processor using triangular-shaped membership function

机译:基于三角隶属度函数的模糊推理处理器的体系结构设计

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The hardware design of a fuzzy processor is always intended to improve its inference performance for real time applications or to reduce the overall cost. The applications of fuzzy logic in various fields have always suffered from a major problem of low speed of operation. The calculation of matching degree always needs very high latency and limits the overall inference performance. In this paper, a novel architecture for calculating the matching between two triangular-shaped membership functions has been proposed. The VHDL implementation of the proposed architecture has been performed. The proposed architecture is more efficient in area and the speed of operation in comparison to a more complex architecture used for the trapezoid-shaped membership function. The proposed architecture has been implemented in a Xilinx Field Programmable Gate Array (FPGA). Further, from the proposed architecture, matching of other type of membership functions can also be obtained easily.
机译:模糊处理器的硬件设计始终旨在提高其在实时应用中的推理性能或降低总体成本。模糊逻辑在各个领域的应用一直遭受操作速度低的主要问题。匹配度的计算始终需要很高的等待时间,并限制了总体推理性能。在本文中,提出了一种新颖的体系结构,用于计算两个三角形隶属函数之间的匹配。所建议架构的VHDL实现已执行。与用于梯形隶属函数的更复杂的体系结构相比,所提出的体系结构在面积和操作速度上更为有效。拟议的架构已在Xilinx现场可编程门阵列(FPGA)中实现。此外,从提出的体系结构中,还可以容易地获得其他类型的隶属函数的匹配。

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