Logarithmic Hyperbolic Cosine for Nonlinear Impulsive Active Noise Control System Using Functional Link Neural Network

The noise canceling performance of conventional active noise control (ANC) system is severely affected by non-Gaussian noise, particularly impulsive noise. The hyperbolic family of adaptive algorithms has seen widespread application in recent years to combat impulsive noise. This paper presents a novel logarithmic hyperbolic cosine adaptive algorithm for impulsive noise in active noise control systems. Additionally, nonlinearity in the system degrades the efficiency of the ANC. We have used the functional link artificial neural network to consider nonlinearity in the system and extended the proposed logarithmic hyperbolic cosine adaptive algorithm to update the functional link artificial neural network. The simulations in the context of nonlinear active noise control systems have been performed to prove the ability of the proposed algorithms to deal with impulsive noise. The proposed algorithm is achieving lower ANR compared to the existing algorithm.