IEEE/CAA Journal of Automatica Sinica
Citation: | Y. B. Wang, C. C. Hua, and P. Park, “Relaxed stability criteria for delayed generalized neural networks via a novel reciprocally convex combination,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 7, pp. 1631–1633, Jul. 2023. doi: 10.1109/JAS.2022.106025 |
[1] |
Y. Chen and G. Chen, “Stability analysis of systems with time-varying delay via a novel Lyapunov functional,” IEEE/CAA J. Autom Sinica, vol. 6, no. 4, pp. 1068–1073, 2019. doi: 10.1109/JAS.2019.1911597
|
[2] |
X. Zhang, Q.-L. Han, X. Ge, and B. Zhang, “Delay-variation-dependent criteria on extended dissipativity for discrete-time neural networks with time-varying delay,” IEEE Trans. Neural Networks and Learning Systems, pp. 1–10, 2021. DOI: 10.1109/TNNLS.2021.3105591
|
[3] |
J. Chen, J. H. Park, and S. Xu, “Improvement on reciprocally convex combination lemma and quadratic function negative-definiteness lemma,” J. Franklin Institute, vol. 359, no. 2, pp. 1347–1360, 2022. doi: 10.1016/j.jfranklin.2021.11.029
|
[4] |
G. Tan and Z. Wang, “α2-dependent reciprocally convex inequality for stability and dissipativity analysis of neural networks with time-varying delay,” Neurocomputing, vol. 463, pp. 292–297, 2021. doi: 10.1016/j.neucom.2021.08.071
|
[5] |
H. Lin, H. Zeng, X. Zhang, and W. Wang, “Stability analysis for delayed neural networks via a generalized reciprocally convex inequality,” IEEE Trans. Neural Networks and Learning Systems, pp. 1–9, 2022. DOI: 10.1109/TNNLS.2022.3144032
|
[6] |
H. B. Zeng, H. C. Lin, Y. He, K. L. Teo, and W. Wang, “Hierarchical stability conditions for time-varying delay systems via an extended reciprocally convex quadratic inequality,” J. Franklin Institute, vol. 357, no. 14, pp. 9930–9941, 2020. doi: 10.1016/j.jfranklin.2020.07.034
|
[7] |
A. Seuret and F. Gouaisbaut, “Delay-dependent reciprocally convex combination lemma,” 2016. [Online]. Available: http://hal.archives-ouvertes.fr/hal-01257670/.
|
[8] |
X. Zhang, Q.-L. Han, and X. Ge, “Novel stability criteria for linear time-delay systems using Lyapunov-Krasovskii functionals with a cubic polynomial on time-varying delay,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 77–85, 2020.
|
[9] |
Y. Wang, “Appendix: Introduction to the main symbols,” 2022. [Online]. Available: http://dx.doi.org/10.13140/RG.2.2.14675.66083/1.
|
[10] |
F. Long, C. Zhang, Y. He, Q. Wang, and M. Wu, “Stability analysis for delayed neural networks via a novel negative-definiteness determination method,” IEEE Trans. Cybernetics, vol. 52, no. 6, pp. 5356–5366, 2022. doi: 10.1109/TCYB.2020.3031087
|
[11] |
X. Zhang, Q.-L. Han, and J. Wang, “Admissible delay upper bounds for global asymptotic stability of neural networks with time-varying delays,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 11, pp. 5319–5329, 2018. doi: 10.1109/TNNLS.2018.2797279
|
[12] |
J. Chen, X. Zhang, J. H. Park, and S. Xu, “Improved stability criteria for delayed neural networks using a quadratic function negative-definiteness approach,” IEEE Trans. Neural Networks and Learning Systems, vol. 33, no. 3, pp. 1348–1354, 2022. doi: 10.1109/TNNLS.2020.3042307
|