Automatic Kernel Weighting for Multikernel Adaptive Filtering: Multiscale Aspects
Automatic Kernel Weighting for Multikernel Adaptive Filtering: Multiscale Aspects
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DOI：
10.1109/icassp.2019.8682934
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
Kwangjin Jeong;M. Yukawa
中科院分区：
文献类型：
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作者：
Kwangjin Jeong;M. Yukawa
提出了一种用于多核自适应滤波的自动核加权技术。多核自适应滤波方法只有在对核进行适当加权时才能充分发挥其潜力。所提出的技术通过使其相关的自相关矩阵的平均特征值彼此相等来平衡核的优势。该方法的总体复杂度较低，因为可以有效地计算出平均特征值。数值计算结果表明，该方法平衡了系数更新，取得了合理的性能。
This paper presents an automatic kernel weighting technique for multikernel adaptive filtering. The full potential of the multikernel adaptive filtering approach can only be achieved when the kernels are weighted appropriately. The proposed technique balances the dominance of the kernels by making the mean eigenvalues of their associated autocorrelation matrices be equal to each other. The overall complexity of the proposed approach is low because the mean eigenvalues can be computed efficiently. The numerical results verify that the proposed technique balances the coefficient updates and yields reasonable performance.