scholarly journals A Variable Step-Size Leaky LMS Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Sihai Zhao ◽  
Jiangye Xu ◽  
Yuyan Zhang
Keyword(s):  
Input Sequence ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Noise Interference ◽  
Parameter Drift ◽  
Fast Convergence Rate ◽  
Variable Step ◽  
Time Average ◽  
Simulation Results

The leaky LMS algorithm has been extensively studied because of its control of parameter drift. This unexpected parameter drift is linked to the inadequacy of excitation in the input sequence. And generally leaky LMS algorithms use fixed step size to force the performance of compromise between the fast convergence rate and small steady-state misalignment. In this paper, variable step-size (VSS) leaky LMS algorithm is proposed. And the variable step-size method combines the time average estimation of the error and the time average estimation of the normalized quantity. Variable step-size method proposed incorporating with leaky LMS algorithm can effectively eliminate noise interference and make the early convergence, and final small misalignments are obtained together. Simulation results demonstrate that the proposed algorithm has better performance than the existing variable step-size algorithms in the unexcited environment. Furthermore, the proposed algorithm is comparable in performance to other variable step-size algorithms under the adequacy of excitation.

A Variable Step Size LMS Adaptive Filtering Algorithm and Simulations Based on Computational Verb Theory

2013 ◽  
Vol 756-759 ◽  
pp. 3972-3976 ◽  
Author(s):  
Li Hui Sun ◽  
Bao Yu Zheng
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Algorithm ◽  
Linear Functional ◽  
Functional Relationship ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Filtering Algorithm ◽  
Variable Step ◽  
Simulation Results

Based on traditional LMS algorithm, variable step LMS algorithm and the analysis for improved algorithm, a new variable step adaptive algorithm based on computational verb theory is put forward. A kind of sectorial linear functional relationship is established between step parameters and the error. The simulation results show that the algorithm has the advantage of slow change which is closely to zero. And overcome the defects of some variable step size LMS algorithm in adaptive steady state value is too large.

A Novel Variable Step Size LMS Algorithm Based on Modified Hyperbolic Tangent and Its Simulation

2012 ◽  
Vol 490-495 ◽  
pp. 1426-1430 ◽  
Author(s):  
Fu Qing Tian ◽  
Rong Luo
Keyword(s):  
Steady State ◽  
Noise Suppression ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Hyperbolic Tangent ◽  
Step Size ◽  
Low Snr ◽  
Variable Step ◽  
Overall Performance ◽  
Simulation Results

In the paper, a new variable step size LMS algorithm based on modified hyperbolic tangent is presented. In the algorithm, the step size is adjusted by the estimation of the autocorrelation between and .The algorithm introduces the compensation monomial to improve the convergence and the parameters to improve the shape and bottom characteristic of hyperbolic tangent. Therefore, the algorithm has faster convergence, better performance of noise suppression，lower steady state error and misadjustment. The theoretical analysis and simulation results all show that the overall performance of the new algorithm exceeds greatly some existent others under low SNR condition.

Simulation Realization of Adaptive Filtering Based on a Normalized LMS Algorithm

2013 ◽  
Vol 373-375 ◽  
pp. 1159-1163
Author(s):  
Ya Feng Li ◽  
Zi Wei Zheng
Keyword(s):  
Adaptive Filtering ◽  
Notch Filter ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Filtering Algorithm ◽  
Adaptive Notch Filter ◽  
Variable Step ◽  
Simulation Results ◽  
Normalized Lms

This paper presents the new algorithm which is an improved normalized variable step size LMS adaptive filtering algorithm. A normalized LMS algorithm with variable step size iterative formula is deduced and at the same time the simulation results prove that the new algorithm has good performance. The LMS adaptive filtering algorithm has been widely used in many applications such as system identification, noise cancellation and the adaptive notch filter ,the paper analyses the application and implement the simulation by matlab. the result shows the proposed algorithm has been applied well.

scholarly journals Adaptive equalizer with zero-noise constrained LMS algorithm

2003 ◽  
Vol 16 (1) ◽  
pp. 127-135
Author(s):  
Bozo Krstajic ◽  
Zdravko Uskokovic ◽  
Ljubisa Stankovic
Keyword(s):  
Computer Simulation ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Adaptive Equalizer ◽  
Variable Step ◽  
Simulation Results

This paper introduces a type of zero-noise constrained LMS (ZN-CLMS) algorithm in an adaptive equalizer. It is a particular case of mismatched noise constrained LMS (NCLMS) algorithm. It is also a variant of variable step-size LMS algorithm, where the step-size rule arises naturally from the constraints. We will show here that the adaptive equalizer based on the ZN-CLMS algorithm has favorable performance. Computer simulation results are provided to support the proposed implementation of the ZNCLMS.

A Variable Step-Size BLMS Adaptive Jamming Cancellation Algorithm Based on FFT

2014 ◽  
Vol 631-632 ◽  
pp. 116-120
Author(s):  
Cun Qian Feng ◽  
Bing Qian Lu
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Adaptive Filter ◽  
High Efficiency ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Variable Step ◽  
Simulation Results

There are a lot of advantages for the traditional LMS algorithm, such as being simple in structure, being good in stability and so on, but this algorithm has defects that its computational complexity increases rapidly with the order of the adaptive filter. In order to apply the LMS algorithm to the adaptive jamming cancellation system, real time of the LMS algorithm must be improved. This paper deals with the signal which segmented into several areas, utilizes the FFT technology to achieve the blocked algorithm, and finally brings variable step-size method into the new algorithm. The high efficiency of the new algorithm is verified by simulation results.

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.

A noise resilient variable step-size LMS algorithm

2008 ◽  
Vol 88 (3) ◽  
pp. 733-748 ◽  
Author(s):  
Márcio Holsbach Costa ◽  
José Carlos Moreira Bermudez
Keyword(s):  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Variable Step

Improved stability performance of a feedback active noise control using a Steiglitz-McBride adaptive notch filter and robust secondary path identification based on variable step size Griffiths LMS algorithm

2021 ◽  
Vol 69 (2) ◽  
pp. 136-145
Author(s):  
S. Roopa ◽  
S.V. Narasimhan
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Notch Filter ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Adaptive Notch Filter ◽  
Active Noise ◽  
Variable Step ◽  
Feedback Active Noise Control

A stable feedback active noise control (FBANC) system with an improved performance in a broadband disturbance environment is proposed in this article. This is achieved by using a Steiglitz-McBride adaptive notch filter (SM-ANF) and robust secondary path identification (SPI) both based on variable step size Griffiths least mean square (LMS) algorithm. The broadband disturbance severely affects not only FBANC input synthesized but also the SPI.TheSM-ANFestimated signal has narrowband component that is utilized for the FBANC input synthesis. Further, the SM-ANF error has broadband component utilized to get the desired signal for SPI. The use of variable step size Griffiths gradient LMS algorithm for SPI enables the removal of broadband disturbance and non-stationary disturbance from the available desired signal for better SPI. For a narrowband noise field, the proposed FBANC improves the convergence rate significantly (20 times) and the noise reduction from 10 dB to 15 dB (50%improvement) over the conventional FBANC (without SM-ANF and variable step size Griffiths LMS adaptation for SPI).

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