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Recurrent neural network-based fuzzy logic system

机译:基于递归神经网络的模糊逻辑系统

摘要

A recurrent, neural network-based fuzzy logic system includes neurons in a rule base layer which each have a recurrent architecture with an output-to-input feedback path including a time delay element and a neural weight. Further included is a neural network-based, fuzzy logic finite state machine wherein the neural network-based, fuzzy logic system has a recurrent architecture with an output-to-input feedback path including at least a time delay element. Still further included is a recurrent, neural network-based fuzzy logic rule generator wherein a neural network receives and fuzzifies input data and provides data corresponding to fuzzy logic membership functions and recurrent fuzzy logic rules.
机译:一种基于神经网络的递归模糊逻辑系统,在规则基础层中包括神经元,每个神经元具有递归结构,该递归结构具有包括时滞元素和神经权重的输出到输入反馈路径。还包括基于神经网络的模糊逻辑有限状态机,其中基于神经网络的模糊逻辑系统具有递归架构,该递归架构具有包括至少一个时延元件的输出到输入反馈路径。还进一步包括基于循环的,基于神经网络的模糊逻辑规则生成器,其中,神经网络接收并模糊输入数据,并提供与模糊逻辑隶属函数和循环模糊逻辑规则相对应的数据。

著录项

  • 公开/公告号US5606646A

    专利类型

  • 公开/公告日1997-02-25

    原文格式PDF

  • 申请/专利权人 NATIONAL SEMICONDUCTOR CORPORATION;

    申请/专利号US19940265194

  • 发明设计人 EMDADUR R. KHAN;FAITH A. UNAL;

    申请日1994-06-24

  • 分类号G06E1/00;G06E3/00;

  • 国家 US

  • 入库时间 2022-08-22 03:10:34

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