Approximations of mappings and application to translational invariant networks

P. Koiran
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引用次数: 2

Abstract

The author studies the approximation of continuous mappings and dichotomies by one-hidden-layer networks, from a computational point of view. The approach is based on a new approximation method, specially designed for constructing small networks. Upper bounds are given on the size of these networks. These results are specialized to the case of transitional invariant networks, i.e., networks whose outputs are unchanged when their inputs are submitted to a translation.<>
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映射的近似及其在平移不变网络中的应用
作者从计算的角度研究了单隐层网络对连续映射和二分类的逼近。该方法基于一种新的近似方法,专为构建小型网络而设计。给出了这些网络大小的上界。这些结果专门用于过渡不变网络的情况,即当其输入提交到翻译时,其输出不变的网络。
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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Control of a robotic manipulating arm by a neural network simulation of the human cerebral and cerebellar cortical processes Neural network training using homotopy continuation methods A learning scheme of neural networks which improves accuracy and speed of convergence using redundant and diversified network structures The abilities of neural networks to abstract and to use abstractions Backpropagation based on the logarithmic error function and elimination of local minima
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