广义自适应神经滤波器在心电信号增强中的应用

1993 IEEE Annual Northeast Bioengineering Conference Pub Date : 1993-03-18 DOI:10.1109/NEBC.1993.404400

Zeeman Z. Zhang, Nirwan Ansari

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引用次数: 1

摘要

本文讨论了一类非线性自适应滤波器——广义自适应神经滤波器(GANFs)，它将堆栈滤波器推广到更大的一类非线性滤波器，并优于堆栈滤波器。它们是基于堆栈滤波器和神经网络的理论。结果表明，gan滤波器比堆叠滤波器具有更好的噪声抑制性能。讨论了GANFs的实现方法，并对其在心电图信号处理中的性能进行了理论分析。

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On generalized adaptive neural filters with application to enhancing EKG signals

A class of nonlinear adaptive filters called generalized adaptive neural filters (GANFs) developed to generalize stack filters to a larger class of nonlinear filters and to outperform stack filters is discussed. They are based on the theory of stack filters and neural networks. It is shown that GANFs have better noise suppression performance than stack filters. The implementation of GANFs is discussed, and the theoretical analysis in regards to the performance of GANFs on EKG signal processing is also presented.<>

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1993 IEEE Annual Northeast Bioengineering Conference

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