Variable Step Size-Least Mean Squared Algorithm for ECG Signal Denoising Considering Baseline Wander Noise and Cyber Attacks

2020 ◽  
Author(s):  
Md Masud Rana ◽  
Tamanna Akter ◽  
Ahmed Abdelhadi
Keyword(s):  
Cyber Attacks ◽  
Variable Step Size ◽  
Signal Denoising ◽  
Ecg Signal ◽  
Step Size ◽  
Variable Step ◽  
Baseline Wander

scholarly journals Efficient reduction of PLI in ECG signal using new variable step size least mean fourth adaptive algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 307
Author(s):  
T. Gowri ◽  
Rajesh Kumar P. ◽  
D.V.R. Koti Reddy
Keyword(s):  
Adaptive Filters ◽  
Vital Role ◽  
Lms Algorithm ◽  
Channel Noise ◽  
Variable Step Size ◽  
Ecg Signal ◽  
Step Size ◽  
Efficient Reduction ◽  
Variable Step ◽  
Cardiac Diagnosis

It is very important in remote cardiac diagnosis to extract pure ECG signal from the contaminated recordings of the signal. When recording the ECG signal in the laboratory, the signal is affected by numerous artifacts. Varies artifacts generally degrades the signal quality are PLI, EM, MA and EM. In addition to these, the channel noise also added when transmitting signal from remote location to diagnosis center for analyzing the signal. There are several approaches are used to reduce the noise present in the ECG signal. From the literature it is proven that compared to non adaptive filters, adaptive filters play vital role to trace the random changes in the corrupted signals. In this paper, we proposed efficient Variable step size leaky least mean fourth algorithm and its sign versions for reducing the complexity. These algorithms shows that it gives low steady state error due to least mean fourth and fast convergence rate that is it tracks the input signal quickly because of its variable step size is high at initial iterations of signal compared to the LMS algorithm. The performance of the algorithm is evaluated using SNR, frequency spectrum, MSE, misadjustment and convergence characteristics.

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

2012 ◽  
Vol 2 (1) ◽  
pp. 35-51 ◽  
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.

A Variable Step-Size for Sparse Nonlinear Adaptive Filters

2021 ◽  
Author(s):  
Alberto Carini ◽  
Markus V. S. Lima ◽  
Hamed Yazdanpanah ◽  
Simone Orcioni ◽  
Stefania Cecchi
Keyword(s):  
Adaptive Filters ◽  
Variable Step Size ◽  
Step Size ◽  
Variable Step

Active control for vehicle interior noise using the improved iterative variable step-size and variable tap-length LMS algorithms

2019 ◽  
Vol 67 (6) ◽  
pp. 405-414 ◽  
Author(s):  
Ningning Liu ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Hui Guo ◽  
Bin Gao ◽  
...  
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Convergence Speed ◽  
Interior Noise ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Vehicle Interior ◽  
Vehicle Interior Noise ◽  
Variable Step

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

Sign in / Sign up

Export Citation Format

Share Document