Analog Propose of Adaptive Filter using all Pass Functions and LMS approach

The adaptive filters has been traditionally developed in digital environment which involves large number of computations to get the coefficients that make the desired approximation. Most of the time, this calculations required a great capacity machines and that is not practical for some applications like channel equalization in cellular systems. This paper shows an alternative way to develop adaptive filters using all-pass functions and applying the LMS algorithm to reduce the error between the reference signal and the adaptive filter output. Simulation results show that the number of coefficients needed to make the approach is smaller than used in digital adaptive filters even in a high filter order, with faster convergence rate.