Adaptive noise cancellation using q-LMS

When a signal is attenuated by some interference or additive noise, adaptive filters provide best solution for the recovery of such signals. Based on adaptive filtering several techniques (algorithms) have been developed in the literature. Due to simplicity, stability, low computational cost and better efficiency, Least Mean Square (LMS) algorithm attract many researchers in this regards. In this paper, a variant of LMS algorithm named q-Least Mean Square (q-LMS) algorithm is investigated for noise cancellation scenario. Moreover, an automatic methodology is adopted for time varying q parameter through which q parameter can adjust itself to get better efficiency and minimize the steady state error. The efficiency of the adopted algorithm is compared with the most widely used (LMS) algorithm by using MATLAB simulations.