APPLYING THE PARTICLE SWARM OPTIMIZATION ALGORITHM (PSO) IN THE DESIGN OF THE ADAPTIVE FILTER

Abstract

The paper has proposed an adaptive filter using particle swarm optimization
algorithm (PSO) and its application to cancelled white noise. This is a new
method to obtain signals with higher quality than previous adaptive filter
methods such as Least Mean Squares (LMS) filter, Normalized Least Mean Square
method (NLMS). The adaptive filter uses the swarm optimization algorithm that
automatically updates the filter coefficients to match to the random and
unknown change of the signal. The simulation results show that, in the case the
filter coefficient increases, the proposed approach achieves higher accuracy than
the LMS algorithm.