自适应非线性FIR主动噪声控制

Adaptive Nonlinear FIR Active Noise Control

针对非线性主动噪声控制系统的非高斯噪声问题,利用Hammerstein/Wiener模型思想简化Volterra滤波器,提出基于函数映射的非线性FIR主动噪声控制器.给出基于二阶Renyi误差熵和均方误差加权和的广义滤波-X梯度下降算法,实现自适应非线性主动噪声控制,并分析了控制算法的收敛性.该方法综合了信息熵和均方误差对误差信息的优势,结构简单且学习参数少.仿真结果表明了该方法的有效性.

A nonlinear FIR active noise controller based on functional mapping is proposed for nonlinear active noise control（ANC） systems,which simplifies the Volterra filter inspiring from Hammerstein/Wiener model.The generalized filtered-X gradient descent algorithm is applied to the proposed controller for the nonlinear,non-Gaussian noises attenuation,which is based on the weighted sum of Renyi＇s quadratic error entropy and mean square error.In addition,the convergence of the proposed approach is analyzed.The overall scheme integrates the advantages of information entropy and mean square error criterion,and it also has the advantages of relative simple structure and less learning parameters.The simulation results demonstrate the validity of the proposed approach.