In order to improve the sparsity exploitation performance of norm constraint least mean square (LMS) algorithms, a novel adaptive algorithm is proposed by introducing a variable p-norm-like constraint into the cost function of the LMS algorithm, which exerts a zero attraction to the weight updating iterations. The parameter p of the p-norm-like constraint is adjusted iteratively along the negat...

A new Lp-norm constraint least mean square (Lp-LMS) algorithm with new strategy of varying p is presented, which is applied to system identification in this letter. The parameter p is iteratively adjusted by the gradient method applied to the root relative deviation of the estimated weight vector. Numerical simulations show that this new algorithm achieves lower steady-state error as well as eq...

Adaptive equalizer is important in transmission of wireless communication. The equalizer using least mean square (LMS) algorithm is adopted. Simulation results show that step size influences the algorithm convergence and stability, which will significantly affect the performance of adaptive equalizer. The requirement of step for convergence speed, time-varying tracking accuracy and convergence ...

Analysis of the leaky least mean square (LMS) adaptive algorithm has justified the use of a leakage factor in many applications. In this work, a similar leakage factor is introduced in the two-channel LMS and the extended LMS (XLMS) algorithms for use in stereophonic acoustic echo cancellation. This is compared with the alternative of adding random white noise to the input stereo signals. Simul...

This paper briefly discussed the principle of the linear constraints minimum variance (LCMV) algorithm and the least mean square (LMS) algorithm on the basis of the construction of an uniform circular antenna array. Then it compared the parameters of the two, such as signal-to-noise ratio, bit error rate, the average error, convergence rate, and so on, and then it was simulated by MATLAB. The s...

The two-dimensional least mean square ( 2 0 LMS) adaptive filters have been recently used in the image processing applications for reducing the noise. I n this paper, a new two-dimensional LMS algorithm is proposed. For the special desires to the linear phase constraint during filtering the images, a n additional linear phase constraint is added to the existing 2 0 LMS algorithms. Compare with ...

This paper presents the comparison between different adaptive algorithms usages in acoustic echo cancellation. This comparison includes the cancellation of echo generated in room using different adaptive algorithms Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Improved Proportionate Normalized Least Mean Square (IPNLMS) and Recursive Least Squares (RLS) Algorithms. The goal of t...