The performance of conventional active noise control (ANC) systems degrades under non-Gaussian conditions. In the recent past, generalized filtered-x maximum correntropy criterion (FxGMCC) algorithm has been widely used to tackle such non-Gaussian noises. However, noise reduction performance of maximum correntropy criterion (MCC) based algorithms degrades due to the high steady-state misalignment. To overcome this limitation, a filtered-x exponential hyperbolic cosine adaptive filter (FxEHCAF) algorithm is proposed in this paper. Later, an affine combination technique has been applied and the corresponding affine FxEHCAF (A-FxEHCAF) algorithm has been developed here showing faster convergence rate in transient state along with low residual error in steady-state. Simulation study shows that the proposed FxEHCAF and A-FxEHCAF algorithms provide enhanced noise control performance over other existing algorithms.

中文翻译：

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基于指数双曲余弦范数的鲁棒有源噪声控制系统

传统主动噪声控制 (ANC) 系统的性能在非高斯条件下会降低。近年来，广义滤波x最大相关熵准则（FxGMCC）算法已被广泛用于解决此类非高斯噪声。然而，基于最大熵准则（MCC）的算法的降噪性能由于高稳态失准而降低。为了克服这一限制，本文提出了一种滤波x指数双曲余弦自适应滤波器（FxEHCAF）算法。后来，应用了仿射组合技术，并开发了相应的仿射 FxEHCAF (A-FxEHCAF) 算法，该算法在瞬态下具有更快的收敛速度，在稳态下具有较低的残差误差。仿真研究表明，所提出的 FxEHCAF 和 A-FxEHCAF 算法比其他现有算法提供了增强的噪声控制性能。