Efficient construction of dictionaries for kernel adaptive filtering in a dynamic environment
Efficient construction of dictionaries for kernel adaptive filtering in a dynamic environment
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DOI：
10.1109/icassp.2015.7178629
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发表时间：
2015-04
期刊：
影响因子：
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通讯作者：
Taichi Ishida;Toshihisa Tanaka
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文献类型：
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作者：
Taichi Ishida;Toshihisa Tanaka
核自适应滤波的主要挑战之一是如何构造一个有效的观测输入信号字典。在本文中，我们提出了新的字典自适应规则的内核自适应滤波。第一种算法可以有效地“移动”字典中的元素以提高逼近性能。第二种算法主要针对非平稳系统，它可以产生字典大小的增加。该方法可以消除字典中不必要的元素。数值例子支持所提出的方法的有效性。
One of the major challenges in kernel adaptive filtering is how to construct an efficient dictionary of observed input signals. In this paper, we propose novel dictionary adaptation rules for kernel adaptive filtering. The first algorithm can efficiently “move” elements of the dictionary to increase the approximation performance. The second algorithm mainly focuses on a nonstationary system, which can yield the increase of the dictionary size. The proposed method can eliminate unnecessary elements in the dictionary. Numerical examples support the efficacy of the proposed methods.