TY - GEN
T1 - Adaptive Random Fourier Features Kernel LMS
AU - Gao, Wei
AU - Chen, Jie
AU - Richard, Cedric
AU - Shi, Wentao
AU - Zhang, Qunfei
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Gaussian kernel
KW - Kernel LMS
KW - random Fourier features
KW - stochastic gradient descent
UR - http://www.scopus.com/inward/record.url?scp=85184853178&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC59353.2023.10400238
DO - 10.1109/ICSPCC59353.2023.10400238
M3 - 会议稿件
AN - SCOPUS:85184853178
T3 - Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
BT - Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
Y2 - 14 November 2023 through 17 November 2023
ER -