Novel Parallel Multiple Minor Components Extraction Algorithm by Diagonal Matrix Method

In this letter, we propose a novel multiple minor components (MCs) extraction algorithm by adding a diagonal matrix into the Douglas minor subspace trascking algorithm. Through analyzing all the characteristics of the fixed points, it is proven that the proposed algorithm is stable if and only if th...

Full description

Saved in:
Bibliographic Details
Published in:Neural processing letters 2023-12, Vol.55 (7), p.8947-8956
Main Authors: Gao, Yingbin, Kong, Xiangyu, Dong, Haidi
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Complex Systems
Computational Intelligence
Computer Science
Eigenvalues
Eigenvectors
Initial conditions
Jamming
Matrix methods
Neural networks
Ordinary differential equations
Parameter estimation
Permutations
Signal processing
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this letter, we propose a novel multiple minor components (MCs) extraction algorithm by adding a diagonal matrix into the Douglas minor subspace trascking algorithm. Through analyzing all the characteristics of the fixed points, it is proven that the proposed algorithm is stable if and only if the state matrix is composed by the desired MCs. Compared with traditional algorithms, the proposed algorithm has two advantages: (1) The initial conditions can be easily satisfied. (2) The permutation of the estimated MCs is explicitly given in prior. Besides, the norm of the state matrix has stability on the manifold, which illustrates that the proposed algorithm has the virtues of anti-jamming capability. Simulation results are presented to further demonstrate the effectiveness of the proposed algorithm.
ISSN:1370-4621
1573-773X
DOI:10.1007/s11063-023-11186-4