Stability analysis of delayed neural network based on the convex method and the non-convex method-Reference-Cited by-同舟云学术

Stability analysis of delayed neural network based on the convex method and the non-convex method

Published:2022-04 Issue: Volume:483 Page:275-285
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Hu Xiaofang,Liu Xinge,Tang Meilan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference43 articles.

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2. Delay-dependent robust stability criteria for uncertain neutral systems with mixed delays;He;Syst. Control Lett.,2004

3. Novel stability criteria for linear time-delay systems using Lyapunov-Krasovskii functionals with a cubic polynomial on time-varying delay;Zhang;IEEE-CAA J. Autom.,2021

4. An overview of recent developments in Lyapunov-Krasovskii functionals and stability criteria for recurrent neural networks with time-varying delays;Zhang;Neurocomputing,2018

5. Global asymptotic stability analysis for delayed neural networks using a matrix quadratic convex approach;Zhang;Neural Netw.,2014

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3. Bifurcation detections of a fractional-order neural network involving three delays;Journal of Applied Mathematics and Computing;2024-01-13

4. Further results on stability analysis of delayed neural networks via a parameter-dependent quadratic function negative-definiteness lemma;International Journal of Systems Science;2023-08-25

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