Adaptive Noise Cancellation Using Improved LMS Algorithm

In order to attain a higher reduction of the interfering noise, and to improve transmission and reception of the signal-to-noise (SNR) ratio adaptive noise cancellation (ANC) is used. In the application of adaptive noise cancellation most widely used adaptive filtering technique is the least mean square (LMS) algorithm. In this paper an improved least mean square algorithm of flexible step length for adaptive noise cancellation is been used to achieve better noise suppression ability and faster convergence. In MATLAB simulation environment adaptive noise cancellation system is been realized using a speech signal with Gaussian white noise as interfering source. Performance of the LMS algorithms with fixed and variable convergence factor is studied along with performance comparison of designed algorithm against conventional LMS, NLMS and RLS.