By increasing the number of layers of the factor analysis model, the factor analysis was able to largely reduce the noise of the ECG signal. That is, the deep factor analysis was an effective tool for the noise reduction of the ECG signal.
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Approach This study proposed a novel ECG signal denoising algorithm based on the deep factor analysis. The major technical innovations include a layer-by-layer ...
ECG signal denoising based on deep factor analysis - Semantic Scholar
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A novel interpretable deep Denoising framework based on sparse representation is proposed in this study, and the half quadratic splitting (HQS) algorithm is ...
Feb 14, 2024 · The efficacy of ECG signal denoising hinges on selecting the optimal WT parameter combination. This selection is formulated as an optimisation ...
This paper introduces a new way to denoise the signal, utilizing deep recurrent neural net- works (DRNN).
Jan 8, 2024 · This paper proposes a denoising method based on an adversarial deep learning approach for the post-processing of multi-channel fetal ...
Objective In telemedicine, dynamic electrocardiogram (ECG) monitoring is important for preventing and diagnosing cardiovascular diseases.
Mar 29, 2020 · In this paper, a method of noise reduction based on deep learning is proposed. The method is divided into two stages, and two corresponding ...
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Antczak [12], proposed using synthetic data to train a deep algorithm for signal denoising and fine-tuning the network parameters to learn higher-level ...
“ECG signal denoising based on deep factor analysis” is a paper by Ge Wang Lin Yang Ming Liu Xin Yuan Peng Xiong Feng Lin Xiuling Liu published in 2020. It has ...