scholarly journals Signal denoising using matching pursuits

1995 ◽  
Vol 97 (5) ◽  
pp. 3310-3311
Author(s):  
Wade Trappe
Keyword(s):  
Signal Denoising ◽  
Matching Pursuits

Ultrasonic Testing Signal Denoising Based on Matching Pursuits

2013 ◽  
Vol 397-400 ◽  
pp. 2215-2218
Author(s):  
Xiu Li Du ◽  
Ying Hua Jiang
Keyword(s):  
White Noise ◽  
Ultrasonic Testing ◽  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Signal Denoising ◽  
Signal To Noise ◽  
Matching Pursuits ◽  
Testing Signal ◽  
Mp Method ◽  
The Relationship

When matching pursuits (MP) method was used for noise suppression of ultrasonic testing signals, the number of matched atoms affects the denoising performance. The relationship between the number of the matched atoms and denoising capability was analyzed, using the root mean square error (RMSE) and improvement of signal-to-noise ratio (SNR) to evaluate denoising performance. The simulated signals with white noise at different SNR and experimental signal with white noise and grain noise were analyzed respectively, and the results show that the MP method can remove the white noise and grain noise effectively. Moreover the best denoising performance can be arrived if the number of matched atoms is appropriate. At last, the selection principle of atoms number is given.

scholarly journals Matching Pursuits with random sequential subdictionaries

2012 ◽  
Vol 92 (10) ◽  
pp. 2532-2544 ◽  
Author(s):  
Manuel Moussallam ◽  
Laurent Daudet ◽  
Gaël Richard
Keyword(s):  
Matching Pursuits

scholarly journals ECG Signal Denoising and Reconstruction Based on Basis Pursuit

2021 ◽  
Vol 11 (4) ◽  
pp. 1591
Author(s):  
Ruixia Liu ◽  
Minglei Shu ◽  
Changfang Chen
Keyword(s):  
Signal To Noise Ratio ◽  
Heart Diseases ◽  
Gaussian White Noise ◽  
Basis Pursuit ◽  
Signal Denoising ◽  
Ecg Signal ◽  
Penalty Term ◽  
Ecg Signals ◽  
Alternating Direction ◽  
Low Pass

The electrocardiogram (ECG) is widely used for the diagnosis of heart diseases. However, ECG signals are easily contaminated by different noises. This paper presents efficient denoising and compressed sensing (CS) schemes for ECG signals based on basis pursuit (BP). In the process of signal denoising and reconstruction, the low-pass filtering method and alternating direction method of multipliers (ADMM) optimization algorithm are used. This method introduces dual variables, adds a secondary penalty term, and reduces constraint conditions through alternate optimization to optimize the original variable and the dual variable at the same time. This algorithm is able to remove both baseline wander and Gaussian white noise. The effectiveness of the algorithm is validated through the records of the MIT-BIH arrhythmia database. The simulations show that the proposed ADMM-based method performs better in ECG denoising. Furthermore, this algorithm keeps the details of the ECG signal in reconstruction and achieves higher signal-to-noise ratio (SNR) and smaller mean square error (MSE).

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