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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...
Filtering electrocardiogram (ECG) signals calls for a filter whose impulse response can be automatically adjusted according to the varying characteristics of the signal and artifacts. In order to eliminate effectively the artifacts in ECG signals, we propose the unbiased linear artificial neural network (ULANN) as a new type of adaptive filter. This paper compares the performance of the ULANN filter...
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