Simulation and Performance Analysis of Adaptive Filter in Real Time Noise over Conventional Fixed Filter

It is stated that the process of digital signal processing, often to deal with some unforeseen signal, noise or time-varying random signals. In this paper it is shown that only by a two FIR and IIR filter of fixed coefficient optimal filtering cant be achieved. Under such circumstances, it is necessary to design adaptive filters, to track the changes of signal and noise. In present work Adaptive Filter uses the filter parameters of a moment ago to automatically adjust the filter parameters of the present moment, to adapt to the statistical properties that signal and noise unknown or random change, in order to achieve optimal filter. Based on in-depth study of adaptive filter, least mean squares and recursive least squares are applied to the noise, and through the simulation results it has proved here that its performance is much better than using conventional methods designed to filter fixed.