Convex combination of the FxAPV algorithm for active impulsive noise control

Conventional active noise control systems suffer from performance degradation when exposed to impulsive interference. Taking the maximum Versoria criterion (MVC) function as the cost function, an MVC-based filtered-x affine projection algorithm is derived by solving the inequality constraint problem. The algorithm has a fast convergence speed when dealing with active impulsive noise control. Subsequently, a convex combinatorial structure is proposed. The stability and computational complexity of the algorithms are analyzed. A genetic algorithm is used to select the appropriate parameters for different algorithms. The simulation results show that the proposed algorithm has a faster convergence rate in addition to a greater average noise reduction. Lastly, the effectiveness of the proposed algorithms is verified experimentally.