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Optimal Leak Factor Selection for the Output-Constrained Leaky Filtered-Input Least Mean Square Algorithm

机译:输出约束泄漏滤波输入最小均方算法的最佳泄漏因子选择

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摘要

The leaky filtered-input least mean square (LFxLMS) algorithm is widely used in active noise control applications to minimize the degradation of attenuation performance due to output saturation distortion. However, the leak factor, which is critical in determining the steady-state error and robustness of the algorithm, is usually selected through trial and error. This letter proposes a leak factor selection approach, which ensures the LFxLMS algorithm converges to its optimal solution under the average-output-power constraint and can be readily derived in practice. Both broadband and narrowband cases are considered in the derivation without the independence assumption, and the simulations are conducted based on real primary and secondary paths to verify its effectiveness.
机译:泄漏过滤输入最小均方(LFXLMS)算法广泛用于主动噪声控制应用,以最小化由于输出饱和失真而导致的衰减性能的劣化。然而,通常通过试验和错误选择泄漏因子在确定算法的稳态误差和鲁棒性时。这封信提出了一种泄漏因子选择方法,可确保LFXLMS算法在平均输出功率约束下收敛到其最佳解决方案,并且可以在实践中容易地衍生。在没有独立假设的情况下,在推导中考虑宽带和窄带案例,并且基于实际的主要和次要路径进行仿真以验证其有效性。

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