Neural networks based approach solving multi-linear systems with M-tensors

In this paper, we propose continuous time neural network and modified continuous time neural networks for solving a multi-linear system with M-tensors. Theoretically, we prove that the presented neural networks are stable in the sense of Lyapunov stability theory. Numerical simulations are presented...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2019-07, Vol.351, p.33-42
Main Authors: Wang, Xuezhong, Che, Maolin, Wei, Yimin
Format: Article
Language:English
Subjects:
[formula omitted]-tensors
Convergence
Multi-linear systems
Neural network
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Summary:In this paper, we propose continuous time neural network and modified continuous time neural networks for solving a multi-linear system with M-tensors. Theoretically, we prove that the presented neural networks are stable in the sense of Lyapunov stability theory. Numerical simulations are presented to show the effectiveness of the proposed neural networks.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2019.03.025