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SELF-TRAINING TYPE NEURO-FUZZY NETWORK ARCHITECTURE AND ELECTRONIC CONTROL METHOD BY SELF-TRAINING FOR ELECTRONIC EQUIPMENT

机译:电子设备的自训式神经模糊网络体系结构及自训的电子控制方法

摘要

PROBLEM TO BE SOLVED: To obtain a new neuro-fuzzy integration architecture capable of realizing on-line self-training. SOLUTION: This architecture is provided with a fuzzy type microcontroller 11 exclusive for fuzzy rule calculation and integrated on a semiconductor together with a non-volatile memory 9 so as to be monolithic, and the same IC is provided with a microprocessor 5, a volatile memory unit 2, and an arbiter block 3 connected to a bus 4 connecting the fuzzy microcontroller 11 and the microprocessor 5 and the volatile memory unit 2. The arbiter block 3 controls access to the volatile memory unit 2 by the microcontroller 5 or the fuzzy microcontroller 11. Then, an additional fuzzy co-processor 6 for fuzzy logical arithmetic processing is connected between the fuzzy microcontroller 11 and the microprocessor 5.
机译:要解决的问题:获得一种能够实现在线自我训练的新的神经模糊集成架构。解决方案:此体系结构配备有模糊类型微控制器11,专用于模糊规则计算,并与非易失性存储器9集成在一起,形成单片,并且同一集成电路还配备有微处理器5,易失性存储器单元2,以及连接到总线4的仲裁器模块3,该总线4连接模糊微控制器11和微处理器5以及易失性存储单元2。仲裁器模块3控制微控制器5或模糊微控制器11对易失性存储单元2的访问。然后,在模糊微控制器11和微处理器5之间连接用于模糊逻辑算术处理的附加模糊协处理器6。

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