{"title":"New Stability Analysis for Neural Networks with Time-Varying Delays","authors":"Miaomiao Yang, Shouming Zhong","volume":88,"journal":"International Journal of Mathematical and Computational Sciences","pagesStart":652,"pagesEnd":656,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/9998052","abstract":"
This paper studies the problem of asymptotically
\r\nstability for neural networks with time-varying delays.By establishing
\r\na suitable Lyapunov-Krasovskii function and several novel sufficient
\r\nconditions are obtained to guarantee the asymptotically stability of the considered system. Finally,two numerical examples are given to illustrate the effectiveness of the proposed main results.<\/p>\r\n","references":"[1] S.Arik Daly,An analysis of exponential stability of delayed neural\r\nnetworks with time-varying delays. Neural Networks.17(2004)\r\n[2] H.J.Cho,J.H.Park,Novel delay-dependent robust stability criterion of\r\ndelayed cellular neural networks,Chaos Solitons Fractals 32(5)(2007)\r\n1194-1200.\r\n[3] H.Gu, H.Jiang, Z.Teng,Existence and global exponential stability of\r\nequilibrium of competitive neural networks with different time-scales\r\nand multiple delays, J.Franklin Inst. 347(2010)719-731.\r\n[4] Y.He,M.Wu,J.H.She,Delay-dependent exponential stability of delayed\r\nneural networks with time-varyingdelays, IEEE Trans. Circuits Syst.II\r\nExp.Briefs 53 (7)(2006)553-557.\r\n[5] Y.He, G.P.Liu, D.Rees, New delay-dependent stability criteria for\r\nneutral networks with time-varying delays, IEEE Trans. Neural\r\nNetw.18(1)(2007)310-314.\r\n[6] Z.Zuo,C.Yang,Y Wang,A new method for stability analysis of recurrent\r\nneural networks with interval time-varying delay,IEEE Trans.Neural\r\nNetworks 21(2)(2010)339-344.\r\n[7] K.Gu,An integral inequality in the stability problem of time delay\r\nsystems,in: Proceedings of 39th IEEE Conference Decision Control,\r\n(2000) 2805-2810.\r\n[8] P.Park, J.W.Ko, C.Jeong,Reciprocally convex approach to stability of\r\nsystems with time-varying delays,Automatica 47(1)(2011)235-238.\r\n[9] Y.H.D, S.M.Zhong, Exponential passivity of BAM neural networks\r\nwith time-varying delays. Applied Mathematics and Computation\r\n221(2013)727-740.\r\n[10] S.Mou, H.Gao, W.Qiang, K.Chen,New delay-dependent exponential\r\nstability for neural networks with time delays,IEEE Transactions on\r\nSystems, Man,and Cybernetics B 38 (2008)571-576.\r\n[11] Zixin L,J. Y,D. Y. X,Triple-integral method for the stability analysis of\r\ndelayed neural networks ,Neurocomputing 99(2013) 283-289.\r\n[12] K.Gu,An integral inequality in the stability problem of time delay\r\nsystems,in: Proceedings of 39th IEEE Conference Decision Control,\r\n(2000) 2805-2810.\r\n[13] Miaomiao Yang,S M Zhong,Improved Exponential Stability Analysis\r\nfor Delayed Recurrent Neural Networks,World Academy of Science,\r\nEngineering and Technology International Journal of Mathematical,\r\nComputational Science and Engineering Vol:8 No:1, (2014)90-96.\r\n[14] O.M. Kwon, S.M. Lee, JuH. Park, E.J. Cha, New approaches on stability\r\ncriteria for neural networks with interval time-varying delays, Appl.\r\nMath. Comput.218 (19) (2012) 9953-9964\r\n[15] H.Y. Shao, Q.L. Han, New delay-dependent stability criteria for neural\r\nnetworks with two additive time-varying delay components, IEEE Trans.\r\nNeural Networks 22 (5) (2011) 812-818.\r\n[16] T Li,X Yang,P Yang,New delay-variation-dependent stability for neural\r\nnetworks with time-varying delay,Neurocomputing 101 (2013) 361-369.\r\n[17] C.C.Hua, C.N.Long, X.P.Guang,New results on stability analysis of\r\nneural networks with time-varying delays, Phys. Lett. A 352(2006)335-\r\n340.\r\n[18] O.M.Kwon,J.H.Park,Improved delay-dependent stability criterion for\r\nneural networks with time-varying delays,Phys.Lett.A 373(2009)529-\r\n535.\r\n[19] J.Sun, G.P.Liu, J.Chen, D.Ree,Networked predictive control for neural\r\nnetworks with time-varying interval delays,Phys.Lett.A 373(2009)342-\r\n348.\r\n[20] Z.X.Liu,J.Y,D.Y.Xu,Triple-integral method for the stability analysis of\r\ndelayed neural networks,Neurocomputing 99 (2013)283-289.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 88, 2014"}