基于BP神经网络的泰勒级数展开系数工程解

Zhongzhong Hu, Helei Wu, Shuyun Zhu
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引用次数: 1

摘要

提出了一种适用于工程应用的求解泰勒级数展开系数的方法:人工神经网络(ANN),它具有高度的非线性和学习能力。变换后的泰勒级数(TS)可以表示为一个标准的三层前馈神经网络,其中权值对应于泰勒系数。因此,可以使用反向传播(BP)算法确定泰勒系数。在这些方法中,我们只需要原始函数的样本空间。因此该方法具有一定的工业应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Engineering Solution to Taylor Series Expansion Coefficients Based on BP Neural Network
One method of obtaining the Taylor Series Expansion Coefficients, which are suitable for engineering application, are presented: Artificial neural network(ANN) , by virtue of its high nonlinear and learning abilities. The Taylor Series ( TS ) can be represented as a standard 3-layers feed-forward neural network after transforming in which the weights are correspond to the Taylor Coefficients. Therefore, the Taylor Coefficients can be determined by using Back Propagation (BP) algorithm. In the methods, we only need the sample space of the original function. So the method have the value of application in industries.
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