Robust Exponential Hyperbolic Secant Algorithm for Active Control Against Impulsive Noise Environments

The effectiveness of conventional active noise control (ANC) system deteriorates significantly when operating against impulsive noise environments. Over the past few years, the hyperbolic family of adaptive filtering algorithms have been extensively applied for suppressing impulsive noise. This work introduces a new exponential hyperbolic secant adaptive filter for active control operation, which is well suited for impulsive noise scenarios. Additionally, the stability condition in relation to the learning rate, steady-state analysis along with the computational complexity are also studied. Simulation outcomes based on measured acoustic paths demonstrate the efficiency of the proposed algorithm under strong and dynamic impulsive environment.