Abstract
Stability is a central issue in the study of dynamical systems, and quaternion-valued neural networks (QVNNs) perform well in handling the problem involving high-dimension date. The paper is dedicated to investigating the stability problem of QVNNs with neutral delay. In order to accurately estimate the derivative of Lyapunov functional, both reciprocally convex inequality and Wirtinger-based inequality are extended to the quaternion domain. And the direct quaternion method is used to analyze the quaternion-valued neutral neural networks (QVNNNs). Based on the generalized inequalities, the existence, uniqueness, and global stability criteria for QVNNS with several freedom matrices are derived. Concision and compact stability criteria of QVNNNs are established in the form of quaternion-valued LMIs, and the correctness of the theoretical results was verified through a numerical example.
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References
Yang X, Li C, Song Q, Chen J, Huang J. Global Mittag-Leffler stability and synchronization analysis of fractional-order quaternion-valued neural networks with linear threshold neurons. Neural Netw. 2018;105:88–103.
Wan A, Hong Q, Peng J, Wang M. Delay-independent criteria for exponential stability of generalized Cohen-Grossberg neural networks with discrete delays. Phys Lett A. 2006;353(2):151–7.
Zhang W, Yang S, Li C, Zhang W, Yang X. Stochastic exponential synchronization of memristive neural networks with time-varying delays via quantized control. Neural Netw. 2018;104:93–103.
Li R, Cao J, Alsaedi A, Alsaadi F. Exponential and fixed-time synchronization of Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms. Appl Math Comput. 2017;313:37–51.
Sheng Y, Huang T, Zeng Z. Exponential stabilization of fuzzy memristive neural networks with multiple time delays via intermittent control. IEEE Trans Syst Man Cybern: Syst. 2022;52(5):3092–101.
Xu C, Liao M, Li P, Guo Y, Liu Z. Bifurcation properties for fractional order delayed BAM neural networks. Cogn Comput. 2021;13(2):322–56.
Wei R, Cao J, Gorbachev S. Fixed-time control for memristor-based quaternion-valued neural networks with discontinuous activation functions. Cogn Comput. 2023;15(1):50–60.
Zhang W, Huang J. Stability analysis of stochastic delayed differential systems with state-dependent-delay impulses: application of neural networks. Cogn Comput. 2022;14(2):805–13.
Arena P, Baglio S, Fortuna L, Xibilia M. Chaotic time series prediction via quaternionic multilayer perceptrons. IEEE International Conference on Systems, Man and Cybernetics, Intelligent Systems for the 21st Century. 1995;1790–4.
Kong G, Guo L. Stability analysis of delayed neural networks based on improved quadratic function condition. Neurocomputing. 2023;524:158–66.
Chen J, Park J, Xu S. Stability analysis for delayed neural networks with an improved general free-matrix-based integral inequality. IEEE Trans Neural Netw Learn Syst. 2019;31(2):675–84.
Zhang Y, Zhou L. Novel global polynomial stability criteria of impulsive complex-valued neural networks with multi-proportional delays. Neural Comput Appl. 2022;34:2913–24.
Song Q, Chen Y, Zhao Z, Liu Y, Alsaadi F. Robust stability of fractional-order quaternion-valued neural networks with neutral delays and parameter uncertainties. Neurocomputing. 2021;420:70–81.
Zhang W, Huang J. Stability analysis of stochastic delayed differential systems with state-dependent-delay impulses: application of neural networks. Cogn Comput. 2022;14(2):805–13.
Liu Y, Zhang D, Lu J, Cao J. Gobal μ-stability criteria for quaternion-valued neural networks with unbounded time-varying delays. Inf Sci. 2016;360:273–88.
You X, Song Q, Liang J, Liu Y, Alsaadi F. Global μ-stability of quaternion-valued neural networks with mixed time-varying delays. Neurocomputing. 2018;290:12–25.
Wu A, Zeng Z, Zhu X, Zhang J. Exponential synchronization of memristor-based recurrent neural networks with time delays. Neurocomputing. 2011;74(17):3043–50.
Dhamala M, Jirsa V, Ding M. Enhancement of neural synchrony by time delay. Phys Rev Lett. 2004;92:074104.
Wu A, Zeng Z. Exponential stabilization of memristive neural networks with time delays. IEEE Trans Neural Netw Learn Syst. 2012;23(12):1919–29.
Yang X, Feng Y, Yiu K, Song Q, Alsaadi F. Synchronization of coupled neural networks with infinite-time distributed delays via quantized intermittent pinning control. Nonlinear Dyn. 2018;94(3):2289–303.
Chen J, Zhang X, Park J, Xu S. Improved stability criteria for delayed neural networks using a quadratic function negative-definiteness approach. IEEE Trans Neural Netw Learn Syst. 2020;33(3):1348–54.
Du F, Lu J. New results on finite-time stability of fractional-order Cohen-Grossberg neural networks with time delays. Asian J Control. 2022;438:107–20.
Hu X, Wang L, Zeng Z, Zhu S, Hu J. Settling-time estimation for finite-time stabilization of fractional-order quaternion-valued fuzzy NNs. IEEE Trans Fuzzy Syst. 2022;30(12):5460–72.
Brayton R. Bifurcation of periodic solutions in a nonlinear difference-differential equation of neutral type. Q Appl Math. 1966;24:215–24.
Zhang Z, Zhang X, Yu T. Global exponential stability of neutral-type Cohen-Grossberg neural networks with multiple time-varying neutral and discrete delays. Neurocomputing. 2022;490:124–31.
Wu X, Liu S, Wang H. Pinning synchronization of fractional memristor-based neural networks with neutral delays and reaction-diffusion terms. Commun Nonlinear Sci Numer Simul. 2023. https://doi.org/10.1016/j.cnsns.2022.107039.
Arik S. New criteria for stability of neutral-type neural networks with multiple time delays. IEEE Trans Neural Netw Learn Syst. 2019;31(5):1504–13.
Jian J, Wang B. Global Lagrange stability for neutral-type Cohen-Grossberg BAM neural networks with mixed time-varying delays. Math Comput Simul. 2015;116:1–25.
Xu D, Tan M. Delay-independent stability criteria for complex-valued BAM neutral-type neural networks with time delays. Nonlinear Dyn. 2017;89:819–32.
Tu Z, Cao J, Alsaedi A, Alsaadi F, Hayat T. Global Lagrange stability of complex-valued neural networks of neutral type with time-varying delays. Complexity. 2016;21:438–50.
Shu J, Xiong L, Wu T, Lu Z. Stability analysis of quaternion-valued neutral-type neural networks with time-varying delay. Mathematics. 2019;7(1):1–23.
Tu Z, Jian J, Wang B. Positive invariant and global exponential attractive sets of a class of neural networks with unbounded time-delays. Commun Nonlinear Sci Numer Simul. 2011;16:3738–45.
Liu Y, Wang Z, Liu X. Global exponential stability of generalized recurrent neural networks with discrete and distributed delays. Neural Netw. 2006;19(5):667–75.
Kwon O, Park M, Lee S, Park J, Cha E. Stability for neural networks with time-varying delays via some new approaches. IEEE Trans Neural Netw Learn Syst. 2013;24(2):181–93.
Zhang C, He Y, Jiang L, Wu M, Zeng H. Stability analysis of systems with time-varying delay via relaxed integral inequalities. Syst Control Lett. 2016;92:52–61.
Seuret A, Gouaisbaut F. Wirtinger-based integral inequality: application to time-delay systems. Automatica. 2013;49(9):2860–6.
Zhang C, He Y, Jiang L, Lin W, Wu M. Delay-dependent stability analysis of neural networks with time-varying delay: a generalized free-weighting-matrix approach. Appl Math Comput. 2017;294:102–20.
Lin H, Zeng H, Zhang X, Wang W. Stability analysis for delayed neural networks via a generalized reciprocally convex inequality. IEEE Trans Neural Netw Learn Syst. 2023. https://doi.org/10.1109/TNNLS.2022.3144032.
Tu Z, Cao J, Alsaedi A, Hayat T. Global dissipativity analysis for delayed quaternion-valued neural networks. Neural Netw. 2017;89:97–104.
Seuret A, Gouaisbaut F. Wirtinger-based integral inequality: application to time-delay systems. Automatica. 2013;49(9):2860–6.
Chen X, Li Z, Song Q, Hu J, Tan Y. Robust stability analysis of quaternion-valued neural networks with time delays and parameter uncertainties. Neural Netw. 2017;91:55–65.
Boyd S, Ghaoui L, Feron E, Balakrishnan V. Linear matrix inequalities in system and control theory. Philadelphia: Society for industrial and applied mathematics; 1994.
Isokawa T, Kusakabe T, Matsui N, Peper F. Quaternion neural network and its application, Knowledge-Based Intelligent Information and Engineering Systems. 7th International Conference, KES. Oxford, UK, September 2003. Proceedings, Part II, Springer, Berlin. 2003;2003:318–24.
Isokawa T, Matsui N, Nishimura H. Quaternionic neural networks: fundamental properties and applications, in Complex-Valued Neural Networks: Utilizing High-Dimensional Parameters. Information Science Reference: Hershey, New York; 2009. p. 411–39.
Wei R, Cao J. Fixed-time synchronization of quaternion-valued memristive neural networks with time delays. Neural Netw. 2019;113:1–10.
Wei R, Cao J. Synchronization control of quaternion-valued memristive neural networks with and without event-triggered scheme. Cogn Neurodyn. 2019;13(5):489–502.
Tu Z, Cao J, Alsaedi A, Ahmad B. Stability analysis for delayed quaternion-valued neural networks via nonlinear measure approach. Nonlinear Anal: Model Control. 2018;23(3):361–79.
Funding
This work was jointly supported by the National Natural Science Foundation of China under Grant No. 11601047, the Natural Science Foundation Project of Chongqing under grant Nos. cstc2021jcyj-msxmX0051, cstc2021jcyj-msxm2025, the Science and Technology Innovation Project of Economic Circle Construction in Chengdu-Chongqing Area under Grant No. KJCX2020047, the Science and Technology Research Program of Chongqing Municipal Education Commission under grant Nos. KJZD-K202201202, KJQN202101228, KJQN202101220, KJZD-M202001201.
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Wu, Y., Tu, Z., Dai, N. et al. Stability Analysis of Quaternion-Valued Neutral Neural Networks with Generalized Activation Functions. Cogn Comput 16, 392–403 (2024). https://doi.org/10.1007/s12559-023-10212-w
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DOI: https://doi.org/10.1007/s12559-023-10212-w