基于2阶Renyi熵的自适应主动噪声控制

在前馈主动噪声控制中,基于均方误差准则的传统算法仅考虑了信号的2阶统计量,忽略了实际存在的非高斯信号,不能满足对非高斯噪声的控制要求.提出基于2阶Renyi熵的滤波X自适应有限脉冲响应 (finite impulse response,FIR)主动噪声控制算法,定义2阶Renyi熵作为性能指标,利用Parzen窗方法估计误差的概率密度函数,给出基于2阶Renyi熵的信息梯度下降算法,实现自适应FIR控制,同时分析了算法的收敛性和计算复杂度.对单频信号和实测宽带非高斯噪声的仿真结果表明该算法能很好地消除非高斯噪声.

Adaptive active noise control based on Renyis quadratic entropy

The classical feedforward active noise control methods with mean-square error criteria only consider second order statistics of signals, but neglect real existing non-Gaussian signals. Therefore, these methods do not perform well for non-Gaussian noises. An adaptive finite impulse response(FIR) controller with filtered X algorithm based on Renyis quadratic entropy is proposed to attenuate the noises. Renyis quadratic entropy is defined as the performance index; and the probability density function of the system error is estimated by Parzen windowing estimation method. Renyis quadratic entropy information gradient descent algorithm is applied to the adaptive FIR controller. In addition, the computational complexity and convergence of the proposed algorithm are analyzed. The simulations of single frequency signal and real non-Guassian broadband noises demonstrate that the proposed scheme can improve the non-Gaussian noises reduction performance.