数字神经网络

A. Redgers, I. Aleksander
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引用次数: 3

摘要

当McCulloch和Pitts第一次研究人工神经网络(ann)时,他们的神经元模型由二进制信号组成,这些信号构成一个总和,然后阈值产生神经元的输出。这个模型很快演变为众所周知的“输入加权和函数”模型。“参数化函数的互联系统”的定义涵盖了许多类型的人工神经网络和神经元模型。这两个函数分别是“输出输入加权和的函数”和“输出寻址内存位置内容的函数”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital neural networks
When McCulloch and Pitts first studied artificial neural networks (ANNs), their neuron model consisted of binary signals contributing to a sum which was then thresholded to produce the output of the neuron. This model quickly evolved to the well known 'function of weighted sum of inputs' model.The definition 'an interconnected system of parameterised functions' covers many types of ANNs and neuron models.The functions are respectively, 'output a function of the weighted sum of inputs', and 'output a function of the contents of the addressed memory location'.
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