A Simulation & Performance Analysis of ANC using Adaptive Filters

One of the main objectives within the adaptive signal processing is the noise suppression, i.e. the detection of information bearing signal in noise. Adaptive filter application ANC (Adaptive Noise Cancellation) using adaptive Filter algorithm is an important basis for signal processing. The device automatically filters out the components of the signal which are not related to the orignal signal means uncorrelated signal in time and passes the similar signal i.e. correlated portions of the signal. Since the output as the orignal signal of the device is determined by the input signal statistics and the properties of the filter here use is automatically adjust to variations in the input signal using adaptive filter algorithms. NLMS (Normalised Least Mean Square) adaptive filtering is used as a further modification in LMS (Least Mean Square algorithm to increase the performance of the system. Signal compared with the reference signal and finds noise free signal i.e. noise in the primary input can be essentially eliminated without signal distortion. Kalman Filter is used for both stationary signal and non stationary signal. This uses step gradient method and provides a recursive solution. RLS (Recursive Least Square) is used for recursive solution. Here Comparison of all three adaptive filters algorithms which find the minimum signal to noise ratio. Computer simulations for all cases are carried out using Mat lab software and experimental results are presented that illustrate the usefulness of Simulation & Performance Analysis of ANC using Adaptive Filters. Index Terms -Adaptive Filter, ANC, Kalman Filter, LM, NLMS, RLS.