An adaptive noise cancellation scheme using particle swarm optimization algorithm

This paper deals with the problem of noise cancellation of speech signals in an acoustic environment. In this regard, generally, different adaptive filter algorithms are employed, many of them may lack the flexibility of controlling the convergence rate, range of variation of filter coefficients, and consistency in error within tolerance limit. In order to achieve these desirable attributes as well as to cancel noise effectively, unlike conventional approaches, we formulate the task of noise cancellation as a coefficient optimization problem whereby we introduce and exploit the particle swarm optimization (PSO) algorithm. In this problem, the PSO is designed to perform the error minimization in frequency domain. The outcomes from extensive experimentations show that the proposed PSO based acoustic noise cancellation method provides high performance in terms of SNR improvements with a satisfactory convergence rate in comparison to that obtained by some of the state-of-the-art methods.