New stability conditions of delayed neural networks via improved Lyapunov-Krasovskii functionals

This paper studies the delay-dependent stability problems of neural networks with time-delays. Firstly, in order to make the constructed function contain more useful information, this paper introduces three types of Lyapunov-Krasovskii functional terms to construct an improved Lyapunov-Krasovskii fu...

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Main Authors: Lin, Huichao, Zeng, Hongbing
Format: Conference Proceeding
Language:English
Subjects:
Biological neural networks
Delays
Lyapunov-Krasovskii functional
Neural networks
Neurons
Numerical stability
Stability analysis
Stability criteria
Symmetric matrices
Time-varying delay
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Zeng, Hongbing
description This paper studies the delay-dependent stability problems of neural networks with time-delays. Firstly, in order to make the constructed function contain more useful information, this paper introduces three types of Lyapunov-Krasovskii functional terms to construct an improved Lyapunov-Krasovskii functional. Then, based on the improved Lyapunov-Krasovskii functional and reciprocal convex integral inequalities, some less conservative stability criteria are derived for the considered neural networks. Finally, a well-known numerical example is provided to demonstrate the superiority of the proposed stability criteria.
doi_str_mv 10.1109/CCDC49329.2020.9164180
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subjects Biological neural networks
Delays
Lyapunov-Krasovskii functional
Neural networks
Neurons
Numerical stability
Stability analysis
Stability criteria
Symmetric matrices
Time-varying delay
title New stability conditions of delayed neural networks via improved Lyapunov-Krasovskii functionals
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