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[一种脑电信号数据压缩与尖峰识别的小波神经网络算法]

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

作者信息

Zhang Y, Liu A, Yu K

机构信息

Department of Computer Science, Wuhan University of Technology, Wuhan 430070.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 1999 Jun;16(2):172-6.

Abstract

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

摘要

提出了一种基于小波神经网络的脑电信号压缩表示及癫痫样棘波识别新方法及其算法。小波网络不仅能有效压缩数据,还能恢复原始信号。此外,从脑电信号的时频等值线中自动检测出棘波和棘慢节律的特征。该方法在电生理信号处理和时频分析领域具有很好的应用价值。

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