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On Approximation by Neural Networks with Optimized Activation Functions and Fixed Weights

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摘要 Recently,Li[16]introduced three kinds of single-hidden layer feed-forward neural networks with optimized piecewise linear activation functions and fixed weights,and obtained the upper and lower bound estimations on the approximation accuracy of the FNNs,for continuous function defined on bounded intervals.In the present paper,we point out that there are some errors both in the definitions of the FNNs and in the proof of the upper estimations in[16].By using new methods,we also give right approximation rate estimations of the approximation by Li’s neural networks.
出处 《Analysis in Theory and Applications》 CSCD 2023年第1期93-104,共12页 分析理论与应用(英文刊)
基金 suppoorted by NSFC (No.12061055).
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