Fast Extraction of Somatosensory Evoked Potential using RLS Adaptive Filter Algorithms

被引：0
|
作者：
Ren, Zhaoli [1 ]
Zou, Yuexian [1 ]
Zhang, Zhiguo [2 ]
Hu, Yong [2 ]
机构：
[1] Peking Univ, Shenzhen Grad Sch, Adv Digital Signal Proc Lab, Shenzhen, Guangdong, Peoples R China
[2] Univ Hong Kong, Dept Orthopaed & Traumatol, Hong Kong, Peoples R China
来源：
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年
关键词：
SEP; Adaptive Filter; RLS-ANC; LMS-ANC;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper evaluates the efficacy of the recursive least squares (RLS) in adaptive noise canceller (RLS-ANC) for fast extraction of somatosensory evoked potentials (SEPs). The RLS-ANC method was verified by simulation of electroencephalography (EEG) and Gaussian noise contaminated SEP signals at different signal-to-noise ratios (SNRs). RLS was found to converge faster than the least mean squares (LMS) algorithm in ANC, i.e. SEP extraction by RLS-ANC required fewer trials than LMS-ANC. Experimental results showed that RLS-ANC with less than 50 trials could provide similar performance in SEP extraction to those extracted by the conventional ensemble averaging with 500 trials even at SNR of - 20dB.
引用
收藏
页码：4444 / +
页数：2
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