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A Novel Approach to Active Noise Control using Normalized Clipped Adaptive Algorithm

机译:归一化裁剪自适应算法的主动噪声控制新方法

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In this paper, an efficient normalization based adaptive algorithm is used for active noise control in mechanical systems in order to reject extensive disturbances. The proposed implementations are suitable in applications like various motors, generators, aircrafts, battle field and elevators, etc where noise reduction is very important. In the experiments, the authors used several variants of the familiar Filtered X Least Mean Square (FXLMS) algorithm. In FXLMS the vector of past inputs is first filtered by the secondary path transfer function, hence it is named as filtered X LMS. These modified results normalized FXLMS (NFXLMS) and normalized clipped FXLMS (NCFXLMS) algorithms, leads to fast convergence, better noise rejection capability. The NCFXLMS algorithm requires only half of the multiplications requires than NFXLMS. This type of low complexity strategy is not used in active noise control application in mechatronic systems. Simulation results prove that the proposed active noise cancellers provide better performance in terms of signal to noise ratio than the conventional FXLMS.
机译:在本文中,一种有效的基于归一化的自适应算法被用于机械系统中的主动噪声控制,以拒绝广泛的干扰。所提出的实施方式适用于诸如降噪非常重要的各种电动机,发电机,飞机,战场和电梯等的应用。在实验中,作者使用了熟悉的过滤X最小均方(FXLMS)算法的几种变体。在FXLMS中,先前输入的向量首先通过辅助路径传递函数进行过滤,因此将其命名为Filtered X LMS。这些修改后的结果归一化FXLMS(NFXLMS)和归一化限幅FXLMS(NCFXLMS)算法,可以实现快速收敛,更好的噪声抑制能力。与NFXLMS相比,NCFXLMS算法只需要一半的乘法运算。这种类型的低复杂度策略不在机电一体化系统的有源噪声控制应用中使用。仿真结果证明,所提出的有源噪声消除器在信噪比方面比传统的FXLMS具有更好的性能。

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