Statistical error modeling of CNN-UM architectures: the binary case

Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications Pub Date : 2002-07-22 DOI:10.1109/CNNA.2002.1035085

P. Foldesy

引用次数: 1

Abstract

In this paper a detailed error model is analyzed of the CNN-UM in a general statistical manner. The locally regular template class is considered and the possibility of erroneous output is expressed from the component nonlinearity and parameter deviation.

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CNN-UM架构的统计误差建模:二进制情况

本文用一般统计方法详细分析了CNN-UM的误差模型。考虑了局部正则模板类，并从组件非线性和参数偏差两方面表达了错误输出的可能性。

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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Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications

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