A recursive least square algorithm for active control of mixed noise

Most currently available active control algorithms target noise sources with relatively singular characteristics such as tonal or wideband noise. However, noise in some practical environments is a mixture of different sounds generated by different sources, where the existing algorithms designed for single noise sources may not be optimal. This kind of noise is generally referred to as mixed noise, and this paper develops a specific active control algorithm for mixed noise based on the recursive least square structure. By minimizing the weighted summation of the logarithmic transformation of posterior errors and taking the commutation error into consideration, the proposed algorithm not only reduces broadband, narrowband and impulse noise successfully, but also mixtures of them. Simulation results demonstrate the superiority of the proposed algorithm over existing algorithms such as the filtered-x least mean square, filtered-x logarithmic least mean square, filtered-x normalized least mean square and filtered weight filtered-x normalized least mean square algorithms in terms of convergence rate and noise reduction