O(n) depth-2 binary addition with feedforward neural nets

S. Vassiliadis, K. Bertels, G. Pechanek
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引用次数: 2

Abstract

In this paper we investigate the reduction of the size of depth-2 feedforward neural networks performing binary addition and related functions. We suggest that 2-1 binary n-bit addition and some related functions can be computed in a depth-2 network of size O(n) with maximum fan-in of 2n+1. Furthermore, we show, if both input polarities are available, that the comparison can be computed in a depth-1 network of size O(1) also with maximum fan-in of 2n+1.<>
O(n)深度-2的前馈神经网络二进制加法
本文研究了深度-2前馈神经网络的二进制加法和相关函数的缩减问题。我们建议2-1二进制n位加法和一些相关函数可以在深度为2的网络中计算,网络大小为O(n),最大扇入为2n+1。此外,我们表明,如果两个输入极性都可用,则可以在大小为O(1)的深度1网络中计算比较,并且最大扇入为2n+1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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