Implementation of Cascaded Adaptive Filters for Noise Cancellation

Adaptive filters are the filters that self adjust their transfer functions according to the error signal requirement.There are two categories of adaptive filters : Linear and non linear.Linear adaptive filters are those adaptive filters that obey the principle of superposition when the parameters are kept fixed. Non linear adaptive filters are those that do not follow the principle of superposition.In this paper I have analyzed the cascaded combination of adaptive filters which would then be used for the purpose of noise cancellation.I have used the least mean square algorithm II. LMS ALGORITHM The Least Mean Square algorithm is based on the stochastic gradient algorithms. The term stochastic gradient algorithm has been used in this context so as to distinguish the Least Mean Square algorithm from the steepest descent method in which the determininstic gradient is used as a recursive component so as to compute the Wiener filter parameters and Wiener solution for inputs that are stochastic in nature. KeywordsLeast Mean Square, cost function,step size,mean squared error