A novel complex neural network model for computing the largest real part of eigenvalues and the corresponding eigenvector of a real matrix

DOI

10.2991/eeeis-16.2017.95How to use a DOI?

Keywords

Complex neural network; real matrix; largest real part; eigenvalue; eigenvector

Abstract

A novel complex neural network modelwasproposed, which can be used to compute the largestreal part of eigenvalues and the corresponding eigenvector of a general real matrixin this work. Because of the smart regulatory factorof the model, the largest real part also can be extracted in the case of all the real parts of eigenvalues less than 0. Meanwhile, the presented paper provides a rigorous mathematical proof for its convergence for a more clear understanding of network dynamic behaviors relating to the computation of the eigenvector and the eigenvalue. Numerical example showsthat the proposed model has good performance for a general real matrix.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rong Ye
AU  - Hang Tan
AU  - Xue-Song Liang
AU  - Ping-Li Wan
PY  - 2016/12
DA  - 2016/12
TI  - A novel complex neural network model for computing the largest real part of eigenvalues and the corresponding eigenvector of a real matrix
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 771
EP  - 779
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.95
DO  - 10.2991/eeeis-16.2017.95
ID  - Ye2016/12
ER  -