**REFERENCES**

[1] B. Kosko, Adaptive bidirectional associative memories, Appl. Optim., 26 (1989), 4947-4960.

[2] B. Kosko, Bi-directional associative memories, IEEE, Trans. Syst. Man Cybern., 18 (1988), 49-60.

[3] Y. Xia, J. Cao, M, Lin, New results on the existence and uniqueness of almost

periodic solution for BAM neural networks with continuously distributed delays,

Chaos Solitons and Fractals, 31 (2007), 928-936.

[4] Z. Zhang, W. Liu, D. Zhou, Global asymptotic stability to a generalized CohenGrossberg

BAM neural networks of neutral type delays, Neural Network, 25 (2012), 94-105.

[5] R. Samidurai, R. Sakthivel and S.M. Anthoni, Global asymptotic stability of

BAM neural networks with mixed delays and impulsive, Appl. Math. Comput., 211 (2009), 113-119.

[6] B. Liu, Global exponential stability for BAM neural networks with time-varying

delays in the leakage terms, Nonlinear Analysis Real World Applications, bf 14 (2013), 559-566.

[7] S. Peng, Global attractive periodic solutions of BAM neural networks with continuously

distributed delays in the leakage terms, Nonlinear Analysis Real World

Applications, 11 (2010), 2141-2151.

[8] Q. Zhu, C. Huang, X. Yang, Exponential stability for stochastic jumping BAM

neural networks with time-varying and distributed delays, Nonlinear Analysis

Hybrid Systems, 5 (2011):52-77.

[9] K. Mathiyalagan, R. Sakthivel, S. M. Anthoni, New robust passivity criteria for

stochastic fuzzy BAM neural networks with time-varying delays, Communications

in Nonlinear Science and Numerical Simulation, 17 (2012), 1392-1407.

[10] C. Bai, Stability analysis of Cohen-Grossberg BAM neural networks with delays

and impulses, Chaos, Solitons and Fractals, 35 (2008), 263-267.

[11] P. Balasubramaniam, C, Vidhya, Global asymptotic stability of stochastic BAM

neural networks with distributed delays and reactionCdiffusion terms, Journal

of Computational and Applied Mathematics, 234 (2010), 3458-3466.

[12] Q. Zhu, R. Rakkiyappan, A. Chandrasekar, Stochastic stability of Markovian

jump BAM neural networks with leakage delays and impulse control, Neurocomputing,

136 (2014), 136-151.

[13] S. Guo, L. Huang, Periodic oscillation for discrete-time Hopfield neural networks,

Physics Letters A, 329 (2004), 199-206.

[14] Y. Liu, Z. Wang, A. Serrano, X. liu, Discrete-time recurrent neural networks

with time varying delays: exponential stability analysis, Physics Letters A, 362

(2007), 480-488.

[15] S. Guo, L. Huang, Exponential stability of discrete-time Holpfield neural networks,

Compu. Math. Appl., 47 (2004), 1249-1256.

[16] M. Bohner, A. Peterson, Dynamic equations on time scales, an introducation

with applications. Birkhauser, Boston (2001).

[17] M. Bohner, A. Peterson , Advances in dynamic equations on time scales. Birkhauser, Boston (2003).

[18] Y. Li, X. Chen, L. Zhao, Stability and existence of periodic solutions to delayed

Cohen-Grossberg BAM neural networks with impulses on time scales. Neurocomputing,

72 (2009), 1621-1630.

[19] Y. Li, L. Zhao, T. Zhang, Global exponential stability and existence of periodic

solution of impulsive Cohen-Grossberg neural networks with distributed delays

on time scales, Neural Process Lett, 33 (2011), 61-81.

[20] M. Hu and L. Wang, Existence and stability of anti-periodic solutions for an impulsive

Cohen-Grossberg SICNNs on time scales, International Journal of Mathematical

and Computer Sciences, 6 (2010), 159-165.

[21] T. Yang, L.B. Yang, The global stability of fuzzy cellular neural networks.IEEE

Trans. Circ. Syst. I , 43 (1996), 880–883.

[22] T. Yang, L. B. Yang, C. W. Wu, L. O. Chua, Fuzzy cellular neural networks: theory.

Proc IEEE Int Workshop Cellular Neural Networks Appl., 181–186 (1996).

[23] T. Yang, L. Yang, C. Wu, L. Chua, Fuzzy cellular neural networks: applications,

In Pro. of IEEE Int. Workshop on Cellular Neural Neworks Appl., 225–230

(1996).

[24] T. Huang, Exponential stability of fuzzy cellular neural networks with distributed

delay. Phys. Lett. A, 351 (2006), 48–52.

[25] T. Huang, Exponential stability of delayed fuzzy cellular neural networks with

diffusion, Chaos Solitons Fractals, 31 (2007), 658-664.

[26] Q. Zhang, R. Xiang, Global asymptotic stability of fuzzy cellular neural networks

with time-varying delays, Phy. Lett. A, 372 (2008), 3971–3977.

[27] K. Yuan, J. Cao, J. Deng, Exponential stability and periodic solutions of fuzzy

cellular neural networks with time-varying delays, Neurocomputing, 69 (2006),

1619-1627.

[28] J. Y. Shao, An anti-periodic solution for a class of recurrent neural networks, J.

Comput. Appl. Math., 228 (2009), 231-237.

[29] J.Y. Shao, Anti-periodic solutions for shunting inhibitory cellular neural networks

with time-varying delays, Phys. Lett. A, 372 (2008), 5011-5016.

[30] Y. K. Li, L. Yang, Anti-periodic solutions for Cohen-Grossberg neural networks

with bounded and unbounded delays, Commun. Nonlinear Sci. Numer. Simulat.,

14 (2009), 3134-3140.

[31] G. Q. Peng, L.H. Huang, Anti-periodic solutions for shunting inhibitory cellular

neural networks with continuously distributed delays, Nonlinear Anal.: Real

World Appl., 10 (2009), 2434-2440.

[32] Q.Y. Fan, W.T. Wang, X.J. Yi, Anti-periodic solutions for a class of nth-order

differential equations with delay, J. Comput. Appl. Math., 230 (2009), 762-769.

[33] G. Guseinov, Integration on time scales, J. Math. Anal. Appl., 285 (2003),

107-127.