[1] Kosko B, Adaptive bidirectional associative memories. Applied optics, 26 (1987) 4947-4960.
[2] Guo Y, Luo Y, Wang W, Luo X. and Ge Ch, Fixed-time synchronization of complex-valued memristive BAM neural network and applications in image encryption and decryption. International Journal of Control, Automation and Systems, 18 (2020) 462-476.
[3] Pan Ch, Hong Q. and Wang X, A Novel Memristive Chaotic Neuron Circuit and Its Application in Chaotic Neural Networks for Associative Memory. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, (2020).
[4] Mao Y. and Cheng K, Hopfield Neural Network Method for Problem of Telescoping Path Optimization of Single-Cylinder Pin-Type Multisection Boom. Mathematical Problems in Engineering, (2019).
[5] Aouiti C, Oscillation of impulsive neutral delay generalized high-order Hopfield neural networks. Neural Computing and Applications, 29(2018) 477-495.
[6] Xu C, Liao M, Li P. and Guo. Y, Bifurcation analysis for simplified five-neuron bidirectional associative memory neural networks with four delays. Neural Processing Letters, 50 (2019) 2219–2245.
[7] Njitacke Z. T. and Kengne J, Nonlinear dynamics of three-neurons-based Hopfield neural networks (HNNs): Remerging Feigenbaum trees, coexisting bifurcations and multiple attractors. Journal of Circuits, Systems and Computers, 28 (2019) 1950121.
[8] Sanchez G, Madrenas J. and Cosp-Vilella J, LEGION-based image segmentation by means of spiking neural networks using normalized synaptic weights implemented on a compact scalable neuromorphic architecture. Neurocomputing, 352 (2019) 106–120.
[9] Berezansky L, Braverman E. and Idels L, New global exponential stability criteria for nonlinear delay differential systems with applications to BAM neural networks. Applied Mathematics and Computation, 243 243 899–910.
[10] Arslan E, Narayanan G, Ali M. S, Arik S. and Saroha S, Controller design for finite-time and fixedtime stabilization of fractional-order memristive complex-valued BAM neural networks with uncertain parameters and time-varying delays. Neural Networks, 130 (2020) 60-74.
[11] Nagamani G, Shafiya M, Soundararajan G. and Prakash M, Robust state estimation for fractionalorder delayed BAM neural networks via LMI approach. Journal of the Franklin Institute, 357 (2020) 4964-4982.
[12] Yu T, Wang H, Cao J. and Yang Y, On impulsive synchronization control for coupled inertial neural networks with pinning control. Neural Processing Letters, (2020) 1-16.
[13] Guo R, Xu S. and Lv W, p th moment stochastic exponential anti-synchronization of delayed complexvalued neural networks. Nonlinear Dynamics, 100 (2020) 1257-1274.
[14] Zu J, Yu Z. and Meng Y, Global exponential stability of high-order bidirectional associative memory (BAM) neural networks with proportional delays. Neural Processing Letters, 51 (2020) 2531-2549.
[15] Kumar R. and Das S, Exponential stability of inertial BAM neural network with time varying impulses and mixed time varying delays via matrix measure approach. Communications in Nonlinear Science and Numerical Simulation, 81 (2020) 105016.
[16] Liu G. Q, Zhou S. M, Li Y. Z. and Cai T. C, Stability conditions concerning neutral-type BAM neural networks with infinite distributed delay. International Journal of Computer Mathematics, (2020) 1-15.
[17] Ge J. and Xu J, Stability and Hopf bifurcation on four-neuron neural networks with inertia and multiple delays. Neurocomputing, 287 (2018) 34-44.
[18] Xu C, Liao M. and Li P, Bifurcation analysis for simplified five-neuron bidirectional associative memory neural networks with four delays. Neural Processing Letters, 50 (2019) 2219-2245.
[19] Li D, Zhang Z. and Zhang X, Periodic solutions of discrete-time Quaternion-valued BAM neural networks. Chaos, Solitons Fractals, 138 (2020) 110144.
[20] Xu C, Aouiti C. and Liu Z, A further study on bifurcation for fractional order BAM neural networks with multiple delays. Neurocomputing, 417 (2020) 501-515.
[21] Hu H. and Huang L, Stability and Hopf bifurcation analysis on a ring of four neurons with delays. Applied Mathematics and Computation, 213 (2009) 587-599.
[22] Wang H, Song Q. and Duan C, LMI criteria on exponential stability of BAM neural networks with both time-varying delays and general activation functions. Mathematics and Computers in Simulation, 81 (2010) 837-850.
[23] Mahmoud M. S. and Xia Y, LMI-based exponential stability criterion for bidirectional associative memory neural networks. Neurocomputing, 74 (2010) 284-290.
[24] Javidmanesh E, Global stability and bifurcation in delayed bidirectional associative memory neural networks with an arbitrary number of neurons. Journal of Dynamic Systems, Measurement, and Control, 139 (2017).
[25] Mohammadzadeh Z, Vaziri A. M, Neural Network Synchronization with Uncertain Coupling Delay Function. In International Conference on Management Science and Engineering Management. Springer, Cham (2019) 211-220.
[26] Marcus C. M. and Westervelt R. M, Stability of analog neural networks with delay. Physical Review A, 39 (1989) 347.
[27] Mohammadinejad H. M. and Moslehi M. H, Stability and Hopf-bifurcating periodic solution for delayed Hopfield neural networks with n neuron. Journal of Applied Mathematics,(2014).
[28] Yi Z, Global exponential stability and periodic solutions of delay Hopfield neural networks. International Journal of Systems Science, 27 (1996) 227-231.
[29] Aouiti C. and Assali E. A, Stability analysis for a class of impulsive high-order Hopfield neural networks with leakage time-varying delays. Neural Computing and Applications, 31(2019) 7781-7803.
[30] Kundu A, Das P. and Roy A. B, Stability, bifurcations and synchronization in a delayed neural network model of n-identical neurons. Mathematics and Computers in Simulation, 121 (2016) 12-33.
[31] Aouiti C, Li X. and Miaadi F, Finite-time stabilization of uncertain delayed-hopfield neural networks with a time-varying leakage delay via non-chattering control. Science China Technological Sciences, 62 (2019) 1111-1122.
[32] Tian Y. and Wang Z, Stability analysis for delayed neural networks based on the augmented Lyapunov-Krasovskii functional with delay-product-type and multiple integral terms. Neurocomputing, 410 (2020) 295-303.
[33] Guan K. and Yang J., Global asymptotic stabilization of cellular neural networks with proportionaldelay via impulsive control. Neural Processing Letters, 50 (2019) 1969-1992.
[34] Nagamani G, Shafiya M, Soundararajan G. and Prakash M, Robust state estimation for fractionalorder delayed BAM neural networks via LMI approach. Journal of the Franklin Institute, 357 (2020) 4964-4982.
[35] Liu G. Q, Zhou S. M, Li Y. Z. and Cai T. C, Stability conditions concerning neutral-type BAM neural networks with infinite distributed delay. International Journal of Computer Mathematics, (2020) 1-15.
[36] Wang X, A Global Hartman-Grobman Theorem. arXiv preprint arXiv:2002.06094, (2020).
[37] Muhammadhaji A. and Teng Z, Synchronization stability on the BAM neural networks with mixed time delays. International Journal of Nonlinear Sciences and Numerical Simulation, 1 (2020).
[38] Zhang Z, Guo R. and Liu X, Fixedtime synchronization for complexvalued BAM neural networks with time delays. Asian Journal of Control, 23 (2021) 298-314.
[39] Lin F. and Zhang Z, Global Asymptotic Synchronization of a Class of BAM Neural Networks with Time Delays via Integrating Inequality Techniques. Journal of Systems Science and Complexity, 33 (2020) 366-382.
[40] Liu J, Jian J. and Wang B, Stability analysis for BAM quaternion-valued inertial neural networks with time delay via nonlinear measure approach. Mathematics and Computers in Simulation, 174 (2020) 134-152.
[41] Mohammadzadeh Z, Vaziri A. M, Azemi A and RabieiMotlagh O, Asymptotic synchronization of a class of continuous and delayed systems using adaptive control, 13th International Conference of Iranian Operations Research Society, Shahrood (6-9 September 2020).