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Novel combination schemes of individual weighting factors sign subband adaptive filter algorithm

机译:单个加权因子符号子带自适应滤波算法的新型组合方案

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摘要

To improve the performance of the recently presented individual weighting factors sign subband adaptive filter (IWF-SSAF) algorithm, its 2 combination algorithms using different step sizes are proposed. The first algorithm is to convexly combine the weight vectors of a large step-size IWF-SSAF filter and a small step-size one;and the second algorithm is to obtain a time-varying step size for the IWF-SSAF by combining a large step size and a small one. The minimization of the sum of the 1(1)-norm of subband errors is used to indirectly update the mixing parameters in these 2 algorithms through a modified sigmoidal function. Moreover, in the first algorithm, to implement a smooth transition from the large step-size IWF-SSAF filter to the small step-size one, the component filters receive a cyclic feedback of the combined weight vector. Both proposed algorithms have almost the same convergence performance, but the second algorithm saves computational cost. Simulation results in impulsive noise scenarios demonstrate the superiority of our proposed algorithms.
机译:为了提高最近提出的单个加权因子符号子带自适应滤波器(IWF-SSAF)算法的性能,提出了两种不同步长的组合算法。第一种算法是将大步长的IWF-SSAF滤波器的权重向量与小步长的凸向量进行凸组合;第二种算法是通过组合大的IWF-SSAF滤波器的时变步长步长和一小。子带误差的1(1)-范数之和的最小值用于通过修改的S型函数间接更新这2种算法中的混合参数。此外,在第一算法中,为了实现从大步长的IWF-SSAF滤波器到小步长的平滑过渡,分量滤波器接收组合权重向量的循环反馈。两种提出的算法都具有几乎相同的收敛性能,但是第二种算法节省了计算成本。脉冲噪声场景中的仿真结果证明了我们提出的算法的优越性。

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