Digital calibration of delta sigma modulator using variable step size LMS based adaptive line enhancer

This paper presents a new method of random noise cancellation for removing artefacts from biomedical signals using an adaptive line enhancer (ALE). The ALE is implemented using proposed time domain variable step size Griffith least mean square (VSGLMS) algorithm. The technique is based on the adaptation of the gradient of the error surface. The method makes both the step size and the gradient free from observation noise and reduces the gradient mis-adjustment error. Here, both the gradient and the scale factor for the step size are free from the input noise effects, which makes the algorithm robust to both stationary and non-stationary observation noise. Further the additional computational load involved for this is marginal. The VSGLMS adaptive filter technique for ALE is tested on noise cancellation of two types of bio-medical signals — separation of electro cardiogram (ECG) signal from a background of electro myogram (EMG) and heart sound signal (HSS) from lung sound signal (LSS). Application of VSGLAM–ALE for the separation of HSS from LSS and ECG from EMG has been demonstrated using synthetic White Gaussian noise (WGN). It is found that VSGLMS–ALE can separate the desired signals like ECG or HSS at an input SNR of -5 dB to 27 dB. The performance of VSGLMS is compared with state-of-the-art least mean square LMS–ALE and normalised LMS–ALE. The results of PSDs, time domain waveforms, and mean square error (MSE) have proven that VSGLMS performs better than advanced techniques.

Download Full-text

Combined kurtosis driven variable step size adaptive line enhancer

ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. ◽

10.1109/icarcv.2004.1469450 ◽

2005 ◽

Author(s):

Guo Yecai ◽

Zhao Junwei

Keyword(s):

Variable Step Size ◽

Step Size ◽

Adaptive Line Enhancer ◽

Variable Step

Download Full-text

Design of Gradient and Variable Step-Size for Fast Adaptive Notch Filter

2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) ◽

10.23919/apsipa.2018.8659449 ◽

2018 ◽

Cited By ~ 1

Author(s):

Yosuke Sugiura ◽

Tetsuya Shimamura

Keyword(s):

Notch Filter ◽

Variable Step Size ◽

Step Size ◽

Adaptive Notch Filter ◽

Variable Step

Download Full-text

A Variable Step-Size for Sparse Nonlinear Adaptive Filters

2020 28th European Signal Processing Conference (EUSIPCO) ◽

10.23919/eusipco47968.2020.9287864 ◽

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

Download Full-text

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

Noise Control Engineering Journal ◽

10.3397/1/376737 ◽

2019 ◽

Vol 67 (6) ◽

pp. 405-414 ◽

Cited By ~ 2

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.

Download Full-text