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	An unbiased linear artificial neural network with normalized adaptive coefficients for filtering noisy ECG signals
	Wu, Y. F. ; Wu YF(吴云峰) ; Rangayyan, R. M.
	2013-12-12
关键词	artificial neural networks adaptive filters ECG
英文摘要	The electrocardiogram (ECG) is the most commonly used signal for diagnostic purposes in medicine. The adaptive filtering technique is suited for filtering ECG signals, which are inherently nonstationary. In this paper, we propose a novel neural-network-based adaptive filter to eliminate high-frequency random noise in ECG signals. We make use of a linear artificial neural network (ANN) with delayed values of the ECG time series as the filter inputs. The ANN does not contain a bias in its summation unit, and the coefficients are normalized. During the learning process, the normalized coefficients are used in the steepest-descent algorithm in order to achieve efficient online filtering of noisy ECG signals.
语种	英语
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/70737]
专题	信息技术－已发表论文
推荐引用方式 GB/T 7714	Wu, Y. F.,Wu YF,Rangayyan, R. M.. An unbiased linear artificial neural network with normalized adaptive coefficients for filtering noisy ECG signals[J],2013.
APA	Wu, Y. F.,吴云峰,&Rangayyan, R. M..(2013).An unbiased linear artificial neural network with normalized adaptive coefficients for filtering noisy ECG signals..
MLA	Wu, Y. F.,et al."An unbiased linear artificial neural network with normalized adaptive coefficients for filtering noisy ECG signals".(2013).

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