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Layered MVL neural networks capable of recognizing translated characters

机译:能够识别翻译字符的分层MVL神经网络

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The multivalued logic (MVL) neurons constituting the layered MVL neural network use MVL operations to produce analog responses to be fed to the respective quantizers. A four-layered MVL neural network model capable of recognizing translated characters is presented. Translation of input characters is easily carried out because MVL neural networks have the unique ability that the input patterns for which such a network has been trained can be reproduced directly from the states of synapse weights. Simulation results showing successful recognition of translated characters are presented.
机译:构成分层MVL神经网络的多值逻辑(MVL)神经元使用MVL操作生成模拟响应,以馈送到各个量化器。提出了一种能够识别翻译字符的四层MVL神经网络模型。输入字符的翻译很容易执行,因为MVL神经网络具有独特的能力,即可以直接从突触权重的状态重现已训练了这种网络的输入模式。仿真结果表明成功识别了翻译的字符。

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