Baseline wander removal in cardiac signals using Variable Step Size Adaptive Noise Cancellers

Attenuation of coherent noise, typically weather generated noise and more specifically swell noise, is a major concern in seismic. Such noise, usually characterized by its low-frequency content and high amplitudes, is a common problem in seismic acquisition and, in particular, for marine data. We propose a multiple-input adaptive noise canceller as a solution to attenuate nonstationary coherent noise. This filter uses multiple noise sequences to estimate the noise contained in each trace. This noise estimate is then subtracted to obtain an estimate of the trace whose coherent noise has been attenuated. For the implementation of the adaptive filter, we use a variable step-size normalized least mean squares algorithm, as it is known for its simplicity and robustness. In addition, we demonstrate that variable step-size is necessary for this filter to adapt to the changing statistics of the seismic data. This method is tested on real marine seismic data and compared to a time-frequency median filter and a second-order high-pass Butterworth filter. We demonstrate that the multiple-input adaptive noise canceller is a powerful and efficient filter to attenuate swell noise while preserving the seismic reflections. Depending on the noise configuration, it can be used either by itself or in combination with a time-frequency median filter to obtain the best results.

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Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province

Energies ◽

10.3390/en13225873 ◽

2020 ◽

Vol 13 (22) ◽

pp. 5873

Author(s):

Olalekan Fayemi ◽

Qingyun Di ◽

Qihui Zhen ◽

Yu L. Wang

Keyword(s):

Data Processing ◽

Noise Removal ◽

Sichuan Province ◽

Real Field ◽

Variable Step Size ◽

Adaptive Processing ◽

Telemetry Data ◽

Step Size ◽

Variable Step ◽

Adaptive Noise

This paper deals with the study of multi-channel adaptive noise cancellation with a focus on its application in electromagnetic (EM) telemetry. We presented new variable step-size least mean square (LMS) techniques: regularized variable step-size LMS and regularized sigmoid variable size LMS, for electromagnetic telemetry data processing. Considering the complexity and spatial distribution of environmental noise, algorithms with multiple reference signals were used to retrieve transmitted EM signals. The feasibility of the regularized variable step size LMS algorithms with numerical simulation was analyzed and presented. The adaptive processing techniques were applied in the recovery of frequency and binary phase shift key modulated signal. The proposed multi-channel adaptive technique achieves fast convergence speed, low mean squared error and is shown to have good convergence characteristics compared to conventional methods. In addition to attaining good results from the multi-channel adaptive filter and performing the signal analysis in real-time, we implemented combined fast effective impulse noise removal techniques. The combination of median and mean filters was effective in removing a wide range of impulsive noises without distorting any other data points. Further, electromagnetic telemetry data were acquired during a drilling operation in Sichuan province, China, for real field application. Data processing workflow was designed for EM telemetry data processing based on the noise characteristics, simulation results and expected result for demodulation. To establish a comprehensive overview, a performance comparison of the acquisition array system is also provided. Conclusively, the introduced multichannel adaptive noise canceling techniques are very effective in recovering transmitted EM telemetry signals.

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A variable step-size adaptive noise canceller using signal to noise ratio as the controlling factor

Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the ◽

10.1109/ssst.2004.1295699 ◽

2004 ◽

Cited By ~ 3

Author(s):

Z. Ramadan ◽

A. Poularikas

Keyword(s):

Signal To Noise Ratio ◽

Controlling Factor ◽

Variable Step Size ◽

Signal To Noise ◽

Step Size ◽

Variable Step ◽

Noise Ratio ◽

Adaptive Noise ◽

Adaptive Noise Canceller

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A New Variable-Step-Size LMS Adaptive Filtering Algorithm and Its Application in Adaptive Noise Jamming Cancellation System

2008 8th International Symposium on Antennas, Propagation and EM Theory ◽

10.1109/isape.2008.4735475 ◽

2008 ◽

Author(s):

Honbing Li ◽

Ningning Tong ◽

Nannan Liu ◽

Bo Tian

Keyword(s):

Adaptive Filtering ◽

Variable Step Size ◽

Step Size ◽

Filtering Algorithm ◽

Variable Step ◽

Adaptive Noise

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Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers

International Journal on Measurement Technologies and Instrumentation Engineering ◽

10.4018/ijmtie.2012010103 ◽

2012 ◽

Vol 2 (1) ◽

pp. 35-51 ◽

Cited By ~ 1

Author(s):

S. Yasmin Fathima ◽

G. V. S. Karthik ◽

M. Zia Ur Rahman ◽

A. Lay-Ekuakille

Keyword(s):

Signal To Noise Ratio ◽

Motion Artifacts ◽

Variable Step Size ◽

Ecg Signal ◽

Large Signal ◽

Signal To Noise ◽

Step Size ◽

Variable Step ◽

Adaptive Noise ◽

Power Line Interference

In this paper several variable step size adaptive filter structures for extracting high resolution electrocardiographic (ECG) signals are presented which estimates the deterministic components of the ECG signal and removes the artifacts. The noise canceller minimizes the mean square error (MSE) between the input noisy ECG signal and noise reference. Different noise canceller structures are proposed to remove diverse forms of artifacts: power line interference, baseline wander, muscle artifacts and electrode motion artifacts. The proposed implementation is suitable real time applications, where large signal to noise ratios with fast convergence are required. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal to noise ratio, convergence rate and MSE.

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