Adaptive Generalized Eigenvector Estimating Algorithm for Hermitian Matrix Pencil
Yingbin Gao
刊名IEEE/CAA Journal of Automatica Sinica
2022
卷号9期号:11页码:1967-1979
关键词Deterministic discrete-time (DDT) generalized eigenvector learning rate online estimation
ISSN号2329-9266
DOI10.1109/JAS.2021.1003955
英文摘要Generalized eigenvector plays an essential role in the signal processing field. In this paper, we present a novel neural network learning algorithm for estimating the generalized eigenvector of a Hermitian matrix pencil. Differently from some traditional algorithms, which need to select the proper values of learning rates before using, the proposed algorithm does not need a learning rate and is very suitable for real applications. Through analyzing all of the equilibrium points, it is proven that if and only if the weight vector of the neural network is equal to the generalized eigenvector corresponding to the largest generalized eigenvalue of a Hermitian matrix pencil, the proposed algorithm reaches to convergence status. By using the deterministic discrete-time (DDT) method, some convergence conditions, which can be satisfied with probability 1, are also obtained to guarantee its convergence. Simulation results show that the proposed algorithm has a fast convergence speed and good numerical stability. The real application demonstrates its effectiveness in tracking the optimal vector of beamforming.
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/49927]  
专题自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
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GB/T 7714
Yingbin Gao. Adaptive Generalized Eigenvector Estimating Algorithm for Hermitian Matrix Pencil[J]. IEEE/CAA Journal of Automatica Sinica,2022,9(11):1967-1979.
APA Yingbin Gao.(2022).Adaptive Generalized Eigenvector Estimating Algorithm for Hermitian Matrix Pencil.IEEE/CAA Journal of Automatica Sinica,9(11),1967-1979.
MLA Yingbin Gao."Adaptive Generalized Eigenvector Estimating Algorithm for Hermitian Matrix Pencil".IEEE/CAA Journal of Automatica Sinica 9.11(2022):1967-1979.
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