Anthony, M.: Discrete Mathematics of Neural Networks. SIAM, Philadelphia (2001)
Arik, S.: Stability analysis of delayed neural networks. IEEE Trans. Circuits Syst. 47(7), 1089–1092 (2000)
Arik, S.: An improved global stability result for delayed cellular neural networks. IEEE Trans. Circuits Syst. 49(8), 1211–1214 (2002)
Arik, S.: An analysis of global asymptotic stability of delayed cellular neural networks. IEEE Trans. Neural Netw. 13(5), 1239–1242 (2002)
Arik, S.: Global asymptotic stability of a larger class of neural networks with constant time delay. Phys. Lett. A 311, 504–511 (2003)
Arik, S.: A modified Lyapunov functional with application to stability of neutral-type neural networks with time delays. J. Franklin Inst. 356(3), 276–291 (2019)
Arik, S.: New criteria for stability of neutral-type neural networks with multiple time delays. IEEE Trans. Neural Netw. Learn. Syst. 31(5), 1–10 (2019)
Arik, S., Tavsanoglu, V.: Equilibrium analysis of delayed CNN’s. IEEE Trans. Circuits Syst. 45(2), 168–171 (1998)
Bartosiewicz, Z.: Exponential stability of nonlinear positive systems on time scales. Nonlinear Anal. Hybrid Syst. 32, 143–150 (2019)
Dong, Z., Wang, X., Zhang, X.: A nonsingular M-matrix-based global exponential stability analysis of higher-order delayed discrete-time Cohen–Grossberg neural networks. Appl. Math. Comput. 385, 125401 (2020)
Faydasicok, O.: New criteria for global stability of neutral-type Cohen–Grossberg neural networks with multiple delays. Neural Netw. 125, 330–337 (2020)
Gaines, R.E., Mawhin, J.: Coincidence Degree and Nonlinear Differential Equations. Springer, Berlin (1977)
Gao, S., Wang, Q., Wu, B.: Existence and global exponential stability of periodic solutions for coupled control systems on networks with feedback and time delays. Commun. Nonlinear Sci. Numer. Simul. 63, 72–87 (2018)
Graupe, D.: Principles of Artificial Neural Networks. World Scientific, Singapore (2007)
He, Z., Li, C., Li, H., Zhang, Q.: Global exponential stability of high-order Hopfield neural networks with state-dependent impulses. Physica A 542, 123434 (2020)
Kharitonov, V.L.: Time-Delay Systems. Springer, Berlin (2013)
Li, Y., Qin, J.: Existence and global exponential stability of periodic solutions for quaternion-valued cellular neural networks with time-varying delays. Neurocomputing 31, 91–103 (2018)
Liu, Y., Huang, J., Qin, Y., Yang, X.: Finite-time synchronization of complex-valued neural networks with finite-time distributed delays. Neurocomputing 416, 152–157 (2020)
Luo, Q., Zeng, Z., Liao, X.: Global exponential stability in Lagrange sense for neutral type recurrent neural networks. Neurocomputing 74, 638–645 (2011)
Ma, Q., Feng, G., Xu, S.: Delay-dependent stability criteria for reaction–diffusion neural networks with time-varying delays. IEEE Trans. Cybern. 43(6), 1913–1920 (2013)
Manivannan, R., Samidurai, R., Cao, J., Alsaedi, A., Alsaadi, F.E.: Global exponential stability and dissipativity of generalized neural networks with time-varying delay signals. Neural Netw. 87, 149–159 (2017)
Martynyuk, A.A., Stamova, I.M.: Stability of sets of hybrid dynamical systems with aftereffect. Nonlinear Anal. Hybrid Syst. 32, 106–114 (2019)
Olfati-Saber, R., Murray, R.M.: Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Autom. Control 49(9), 1520–1533 (2004)
Ozcan, N.: New conditions for global stability of neutral-type delayed Cohen–Grossberg neural networks. Neural Netw. 106, 1–7 (2018)
Ozcan, N.: Stability analysis of Cohen–Grossberg neural networks of neutral-type: multiple delays case. Neural Netw. 113, 20–27 (2019)
Roska, T., Wu, C.W., Chua, L.O.: Stability of cellular neural networks with dominant nonlinear and delay-type templates. IEEE Trans. Circuits Syst. 44(4), 270–272 (1993)
Ruan, D., Huang, Z., Guo, X.: Inequalities and stability of stochastic Hopfield neural networks with discrete and distributed delays. Neurocomputing 407, 281–291 (2020)
Samidurai, R., Rajavel, S., Sriraman, R., Cao, J., Alsaedi, A., Alsaadi, F.E.: Novel results on stability analysis of neutral-type neural networks with additive time-varying delay components and leakage delay. Int. J. Control. Autom. Syst. 15(4), 1888–1900 (2017)
Samli, R., Arik, S.: New results for global stability of a class of neutral-type neural systems with time delays. Appl. Math. Comput. 210, 564–570 (2009)
Shi, K., Zhong, S., Zhu, H., Liu, X., Zeng, Y.: New delay-dependent stability criteria for neutral-type neural networks with mixed random time-varying delays. Neurocomputing 168, 896–907 (2015)
Shi, M., Guo, J., Huang, C.: Global exponential stability of delayed inertial competitive neural networks. Adv. Differ. Equ. 2020, 87 (2020). https://doi.org/10.1186/s13662-019-2476-7
Song, Q., Long, L., Zhao, Z., Liu, Y., Alsaadi, F.E.: Stability criteria of quaternio-valued neutral-type delayed neural networks. Neurocomputing 412, 287–294 (2020)
Song, Q., Yu, Q., Zhao, Z., Liu, Y., Alsaadi, F.E.: Boundedness and global robust stability analysis of delayed complex-valued neural networks with interval parameter uncertainties. Neural Netw. 103, 55–62 (2018)
Sun, M., Liu, J.: A novel noise-tolerant Zhang neural network for time-varying Lyapunov equation. Adv. Differ. Equ. 2020, 116 (2020). https://doi.org/10.1186/s13662-020-02571-7
Wang, Y., Lou, J., Yan, H., Lu, J.: Stability criteria for stochastic neural networks with unstable subnetworks under mixed switchings. Neurocomputing (2020, in press)
Weera, W., Niamsup, P.: Novel delay-dependent exponential stability criteria for neutral-type neural networks with non-differentiable time-varying discrete and neutral delays. Neurocomputing 173, 886–898 (2016)
Xiao, Q., Huang, T.: Stability of delayed inertial neural networks on time scales: a unified matrix-measure approach. Neural Netw. 130, 33–38 (2020)
Yang, B., Wang, J., Wang, J.: Stability analysis of delayed neural networks via a new integral inequality. Neural Netw. 88, 49–57 (2017)
Yogambigai, J., Syed Ali, M., Alsulami, H., Alhodaly, M.S.: Global Lagrange stability for neutral-type inertial neural networks with discrete and distributed time delays. Chin. J. Phys. 65, 513–525 (2020)
Zhang, G., Wang, T., Li, T., Fei, S.: Multiple integral Lyapunov approach to mixed-delay-dependent stability of neutral neural networks. Neurocomputing 275, 1782–1792 (2018)
Zhang, G., Zeng, Z., Hu, J.: New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays. Neural Netw. 97, 183–191 (2018)
Zhang, J., Huang, C.: Dynamics analysis on a class of delayed neural networks involving inertial terms. Adv. Differ. Equ. 2020, 120 (2020). https://doi.org/10.1186/s13662-020-02566-4
Zhang, X., Han, Q., Zeng, Z.: Hierarchical type stability criteria for delayed neural networks via canonical Bessel–Legendre inequalities. IEEE Trans. Cybern. 48(5), 1660–1671 (2018)
Zhang, Z., Liu, W., Zhou, D.: Global asymptotic stability to a generalized Cohen–Grossberg BAM neural networks of neutral type delays. Neural Netw. 25, 94–105 (2012)