正则中心高斯网络对C/sup 2/函数的最佳逼近及其误差界

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) Pub Date : 1994-06-27 DOI:10.1109/ICNN.1994.374595

Binfan Liu, J. Si

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引用次数: 6

摘要

在最佳逼近意义上，高斯神经网络可以近似任何C/sup 2/函数，并支持单位超立方体I/sub m/=[0,1]/sup m/。本文给出了一个具有N/sup m/个隐藏神经元的高斯网络的近似误差的上界(0(N/sup -2/))，这些神经元的中心定义在I/ sup / /的规则网格上。

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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The best approximation to C/sup 2/ functions and its error bounds using regular-center Gaussian networks

Gaussian neural networks are considered to approximate any C/sup 2/ function with support on the unit hypercube I/sub m/=[0,1]/sup m/ in the sense of best approximation. An upper bound (0(N/sup -2/)) of the approximation error is obtained in the present paper for a Gaussian network having N/sup m/ hidden neurons with centers defined on a regular mesh in I/sub m/.<>

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Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)

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