Adaptive Random Fourier Features Kernel LMS

Wei Gao, Jie Chen, Cedric Richard, Wentao Shi, Qunfei Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

We propose the adaptive random Fourier features Gaussian kernel LMS (ARFF-GKLMS). Like most kernel adaptive fil-Ters based on stochastic gradient descent, this algorithm uses a preset number of random Fourier features to save computation cost. However, as an extra flexibility, it can adapt the inherent kernel bandwidth in the random Fourier features in an online manner. This adaptation mechanism allows to alleviate the problem of selecting the kernel bandwidth beforehand for the benefit of an improved tracking in non-stationary circumstances. Simulation results confirm that the proposed algorithm achieves a performance improvement in terms of convergence rate, error at steady-state and tracking ability over other kernel adaptive filters with preset kernel bandwidth.

源语言英语
主期刊名Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350316728
DOI
出版状态已出版 - 2023
活动2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023 - Zhengzhou, Henan, 中国
期限: 14 11月 202317 11月 2023

出版系列

姓名Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023

会议

会议2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
国家/地区中国
Zhengzhou, Henan
时期14/11/2317/11/23

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