Existence and global exponential stability of equilibrium for discrete-time fuzzy BAM neural networks with variable delays and impulses

In this paper, we study a class of discrete-time fuzzy BAM neural networks with variable delays and impulses. Based on M-matrix theory and analytic methods, some sufficient conditions are established for the existence and global exponential stability of a unique equilibrium. Moreover, the exponential convergence rate index is estimated. A numerical example is given to show the effectiveness of the obtained results. In particular, the simulation figures establish that fuzzy systems do have more advantages than non-fuzzy systems.

[1]  L.O. Chua,et al.  Cellular neural networks , 1993, 1988., IEEE International Symposium on Circuits and Systems.

[3]  Kohei Kawakami,et al.  Separable 2D Lifting Using Discrete-Time Cellular Neural Networks for Lossless Image Coding , 2005, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[4]  Li Wan,et al.  Impulsive effects on stability of Cohen–Grossberg-type bidirectional associative memory neural networks with delays , 2009 .

[5]  Giuseppe Grassi On the design of discrete-time cellular neural networks with circulant matrices , 2000 .

[6]  Tingwen Huang Exponential stability of delayed fuzzy cellular neural networks with diffusion , 2007 .

[7]  Chunrui Zhang,et al.  Global existence of periodic solutions on a simplified BAM neural network model with delays , 2008 .

[8]  B Kosko,et al.  Adaptive bidirectional associative memories. , 1987, Applied optics.

[9]  Ta-lun Yang,et al.  The global stability of fuzzy cellular neural network , 1996 .

[10]  S. Mohamad Global exponential stability in continuous-time and discrete-time delayed bidirectional neural networks , 2001 .

[11]  Xue-Zhong He,et al.  Delay-independent stability in bidirectional associative memory networks , 1994, IEEE Trans. Neural Networks.

[12]  A. Dembo,et al.  High-order absolutely stable neural networks , 1991 .

[13]  Zhenkun Huang,et al.  Global exponential stability of BAM neural networks with transmission delays and nonlinear impulses , 2008 .

[14]  Chen An,et al.  The Global Stability of Fuzzy Cellular Neural Networks , 2001 .

[15]  Zhengqiu Zhang,et al.  Global exponential stability of interval general BAM neural networks with reaction-diffusion terms and multiple time-varying delays , 2011, Neural Networks.

[16]  BART KOSKO,et al.  Bidirectional associative memories , 1988, IEEE Trans. Syst. Man Cybern..

[17]  Sabri Arik,et al.  Global asymptotic stability analysis of bidirectional associative memory neural networks with time delays , 2005, IEEE Transactions on Neural Networks.

[18]  Te-Jen Su,et al.  Particle Swarm Optimization for Image Noise Cancellation , 2006, First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06).

[19]  Chuandong Li,et al.  Impulsive effects on stability of high-order BAM neural networks with time delays , 2011, Neurocomputing.

[20]  Pagavathigounder Balasubramaniam,et al.  On exponential stability results for fuzzy impulsive neural networks , 2010, Fuzzy Sets Syst..

[21]  Yongkun Li Global exponential stability of BAM neural networks with delays and impulses , 2005 .

[22]  Sabri Arik,et al.  Global Robust Stability of Bidirectional Associative Memory Neural Networks With Multiple Time Delays , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[23]  V. Tavsanoglu,et al.  A new approach to emulate CNN on FPGAs for real time video processing , 2008, 2008 11th International Workshop on Cellular Neural Networks and Their Applications.

[24]  Leon O. Chua,et al.  Fuzzy cellular neural networks: theory , 1996, 1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96).

[25]  Te-Jen Su,et al.  Particle Swarm Optimization for Image Noise Cancellation , 2006, ICICIC.

[26]  H. Aomori,et al.  Hybrid lifting scheme using discrete-time cellular neural networks for lossless image coding , 2005, Proceedings of the 2005 European Conference on Circuit Theory and Design, 2005..

[27]  Xuyang Lou,et al.  Robust asymptotic stability of uncertain fuzzy BAM neural networks with time-varying delays , 2007, Fuzzy Sets Syst..

[28]  Nan Ding,et al.  Dynamic analysis of stochastic bidirectional associative memory neural networks with delays , 2007 .

[29]  Pagavathigounder Balasubramaniam,et al.  Robust exponential stability of uncertain fuzzy Cohen-Grossberg neural networks with time-varying delays , 2010, Fuzzy Sets Syst..

[30]  G. Grassi,et al.  On discrete-time cellular neural networks for associative memories , 2001 .

[31]  A. Tesi,et al.  New conditions for global stability of neural networks with application to linear and quadratic programming problems , 1995 .

[32]  S. Sivasundaram,et al.  Stability properties of the Hopfield-type neural networks , 1993 .

[33]  K. Gopalsamy,et al.  Exponential stability of continuous-time and discrete-time cellular neural networks with delays , 2003, Appl. Math. Comput..

[34]  Jinde Cao,et al.  Discrete-time bidirectional associative memory neural networks with variable delays , 2005 .

[35]  Wansheng Tang,et al.  Exponential stability of fuzzy cellular neural networks with constant and time-varying delays , 2004 .

[36]  K. Gopalsamy,et al.  Dynamics of a class of discete-time neural networks and their comtinuous-time counterparts , 2000 .

[37]  M. Brucoli,et al.  Discrete-time cellular neural networks for associative memories with learning and forgetting capabilities , 1995 .

[38]  Jigen Peng,et al.  A new stability criterion for discrete-time neural networks: Nonlinear spectral radius , 2007 .

[39]  Diego Cabello,et al.  Design of multilayer discrete time cellular neural networks for image processing tasks based on genetic algorithms , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).

[40]  Eva Kaslik,et al.  Impulsive hybrid discrete-time Hopfield neural networks with delays and multistability analysis , 2011, Neural Networks.

[41]  Jinde Cao,et al.  Exponential stability and periodic solutions of fuzzy cellular neural networks with time-varying delays , 2006, Neurocomputing.

[42]  Tsuyoshi Otake,et al.  The template optimization of discrete time CNN for image compression and reconstruction , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[43]  Hubert Harrer Discrete time cellular neural networks , 1992, Int. J. Circuit Theory Appl..

[44]  J. Cao,et al.  Periodic oscillatory solution of bidirectional associative memory networks with delays. , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[45]  Engang Tian,et al.  Delay-dependent stability analysis and synthesis of uncertain T-S fuzzy systems with time-varying delay , 2006, Fuzzy Sets Syst..

[46]  Lin-Bao Yang,et al.  Cellular neural networks: theory , 1988 .

[47]  M. Brucoli,et al.  A global approach to the design of discrete-time cellular neural networks for associative memories , 1996 .

[48]  Nikitas J. Dimopoulos,et al.  A study of the asymptotic behavior of neural networks , 1989 .

[49]  Jinde Cao,et al.  Dynamical behaviors of discrete-time fuzzy cellular neural networks with variable delays and impulses , 2008, J. Frankl. Inst..

[50]  Jinde Cao,et al.  Stability Analysis of Markovian Jump Stochastic BAM Neural Networks With Impulse Control and Mixed Time Delays , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[51]  Xiaodi Li,et al.  Exponential and almost sure exponential stability of stochastic fuzzy delayed Cohen-Grossberg neural networks , 2012, Fuzzy Sets Syst..

[52]  Victor M. Brea,et al.  Design of the processing core of a mixed-signal CMOS DTCNN chip for pixel-level snakes , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[53]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.