On the development of adaptive hybrid active noise control system for effective mitigation of nonlinear noise
On the development of adaptive hybrid active noise control system for effective mitigation of nonlinear noise
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DOI：
10.1016/j.sigpro.2011.08.016
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发表时间：
2012-02
期刊：
影响因子：
--
通讯作者：
Nithin V. George;G. Panda
中科院分区：
文献类型：
--
作者：
Nithin V. George;G. Panda
非线性和声反馈的存在使传统的基于滤波x LMS（FxLMS）算法的有源噪声控制（ANC）系统的抵消性能恶化。为了提高ANC系统的性能，本文提出了一种基于自适应IIR滤波器和函数链接人工神经网络（FLANN）凸组合的滤波SU LMS（FsuLMS）算法的ANC系统。推导了相应的ANC系统的学习算法，并将其用于仿真研究中的性能评估。仿真研究表明，所提出的系统的增强性能，其组件过滤器。
The presence of nonlinearities as well as acoustic feedback deteriorates the cancellation performance of the conventional filtered-x LMS (FxLMS) algorithm based active noise control (ANC) systems. With an objective to improve the performance, a novel filtered-su LMS (FsuLMS) algorithm based ANC system which employs a convex combination of an adaptive IIR filter with a functional link artificial neural network (FLANN) is proposed in this paper. The corresponding learning algorithm of the ANC system is derived and used in the simulation study for performance evaluation. Simulation study reveals enhanced performance of the proposed system over that of its component filters.