Elsevier

Neural Networks

Volume 130, October 2020, Pages 33-38
Neural Networks

Stability of delayed inertial neural networks on time scales: A unified matrix-measure approach

https://doi.org/10.1016/j.neunet.2020.06.020Get rights and content
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Abstract

This note introduces a unified matrix-measure concept to study the stability of a class of inertial neural networks with bounded time delays on time scales. The novel matrix-measure concept unifies the classic matrix-measure and the generalized matrix-measure concept. One sufficient global exponential stability criterion is obtained based on this key matrix-measure and no Lyapunov function is required. To make the stability performance better, another stability criterion in which more detailed information is involved has been acquired. The theoretical results in this note contain and extend some existing continuous-time and discrete-time works. A numerical example is given to show the validity of the results.

Keywords

Stability
Inertial neural network
Time scale
Unified matrix-measure
Time delay

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