Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays

Neural Networks

Volumn 48, Issue , 2013, Pages 195-203

  Wen, Shiping ^a,b,c   Bao, Gang ^d   Zeng, Zhigang ^a,b   Chen, Yiran ^e   Huang, Tingwen ^c  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^c TEXAS A AND M UNIVERSITY AT QATAR   (Qatar)

^d Three Geoges University   (China)

^e UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Memristor; Recurrent neural networks; Synchronization; Time varying delays

Indexed keywords

FUZZY INFERENCE; LYAPUNOV METHODS; MEMRISTORS; SYNCHRONIZATION; TIME DELAY; TIME VARYING CONTROL SYSTEMS; TIME VARYING NETWORKS;

FUZZY MODELING; FUZZY THEORY; GLOBAL EXPONENTIAL SYNCHRONIZATIONS; MEMRISTOR; PARALLEL DISTRIBUTED COMPENSATION; STATE-DEPENDENT; TIME VARYING- DELAYS;

RECURRENT NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; FUZZY SYSTEM; GLOBAL EXPONENTIAL SYNCHRONIZATION; INFORMATION PROCESSING; LYAPUNOV METHOD; MACHINE LEARNING; MATHEMATICAL COMPUTING; MEMRISTOR BASED RECURRENT NEURAL NETWORK; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SYSTEM ANALYSIS;

MEMRISTOR; RECURRENT NEURAL NETWORKS; SYNCHRONIZATION; TIME-VARYING DELAYS;

ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; FUZZY LOGIC; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS;

EID: 84887376596     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2013.10.001     Document Type: Article

References (44)

1. Ananthanarayanan, R., Eser, S., Simon, H., & Modha, D. (2009). In Proceedings of 2009 IEEE/ACM conference high performance networking computing.
2. Arik S. Global robust stability analysis of neural networks with discrete time delays. Chaos, Solitons and Fractals 2005, 26:1407-1414.
3. Balasubramaniam P., Kalpana K., Rakkiyappan R. Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays. Chinese Physics B 2012, 21:048402.
4. Bao G., Wen S., Zeng Z. Robust stability analysis of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument of generalized type. Neural Networks 2012, 33:32-41.
5. Cao J., Chen G., Li P. Global synchronization in an array of delayed neural networks with hybrid coupling. IEEE Transactions on Systems, Man, and Cybernetics, Part B 2008, 38:488-498.
6. Cao J., Huang D., Qu Y. Global robust stability of delayed recurrent neural networks. Chaos, Solitons and Fractals 2005, 23:221-229.
7. Cao J., Wang J. Global asymptotic and robust stability of recurrent neural networks with time delays. IEEE Transactions on Circuits and Systems I 2005, 52:417-426.
8. Cao J., Yuan K., Li H. Global asymptotical stability of recurrent neural networks with multiple discrete delays and distributed delays. IEEE Transactions on Neural Networks 2006, 17:1646-1651.
9. Chen A., Cao J., Huang L. An estimation of upper bound of delays for global asymptotic stability of delayed Hopfield neural networks. IEEE Transactions on Circuits and Systems I 2002, 49:1028-1032.
10. Chiu C., Chiang T. Robust output regulation of T-S fuzzy systems with multiple time-varying state and input delays. IEEE Transactions on Fuzzy Systems 2009, 17:962-975.
11. Choi T., Shi B., Boahen K. An on-off orientation selective address event representation image transceiver chip. IEEE Transactions on Circuits and Systems I 2004, 51:342-353.
12. Chua L.O. Memristor-the missing circuit element. IEEE Transactions on Circuit Theory 1971, 18:507-519.
13. Dong J., Wang Y., Yang G. Control synthesis of continuous-time T-S fuzzy systems with local nonlinear models. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics 2009, 39:1245-1258.
14. Ensari T., Arik S. New results for robust stability of dynamical neural networks with discrete time delays. Expert Systems with Applications 2010, 37:5925-5930.
15. Faydasicok O., Arik S. A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks. Neural Networks 2013, 44:64-71.
16. Forti M., Nistri P. Global convergence of neural networks with discontinuous neuron activations. IEEE Transactions on Circuits and Systems I 2003, 50:1421-1435.
17. Gergel-Hackett N., Hamadani B., Suehle J., Richter C., Hacker C., Gundlach D. A flexible solution-processed memristor. IEEE Electron Device Letters 2009, 30:706-708.
18. Hu S., Wang J. Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks. IEEE Transactions on Automatic Control 2002, 47:802-807.
19. Huang H., Cao J. On global asymptotic stability of recurrent neural networks with time-varying delays. Applied Mathematics and Computation 2003, 142:143-154.
20. Indiveri G. A neuromorphic VLSI device for implementing 2-D selective attention systems. IEEE Transactions on Neural Networks 2001, 12:1455-1463.
21. Jo S., Chang T., Ebong I., Bhadviya B., Mazumder P., Lu W. Nanoscale memristor device as synapse in neuromorphic systems. Nanotechnology Letters 2010, 10:1297-1301.
22. Li S., Ge Z. Fuzzy modeling and synchronization of two totally different chaotic systems via novel fuzzy model. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics 2011, 41:1015-1026.
23. Li T., Fei S., Zhu Q. Design of exponential state estimator for neural networks with distributed delays. Nonlinear Analysis: Real World Applications 2009, 10:1229-1242.
24. Liu S., Douglas R. Temporal coding in a silicon network of integrate-and-fire neurons. IEEE Transactions on Neural Networks 2004, 15:1305-1314.
25. Liu X., Zhong S. T-S fuzzy model-based impulsive control of chaotic systems with exponential decay rate. Physics Letters A 2007, 370:260-264.
26. Ozcan N., Arik S. Global robust stability analysis of neural networks with multiple time delays. IEEE Transactions on Circuits and Systems I 2006, 153:166-176.
27. Park C., Cho Y. T-S model based indirect adaptive fuzzy control using online parameter estimation. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics 2004, 34:2293-2302.
28. Park M., Kwon O., Park J., Lee S., Cha E. Synchronization criteria for coupled neural networks with interval time-varying delays and leakage delay. Applied Mathematics and Computation 2012, 218:6762-6775.
29. Rakkiyappan R., Balasubramaniam P., Cao J. Global exponential stability results for neutral-type impulsive neural networks. Nonlinear Analysis: Real World Applications 2010, 11:122-130.
30. Sharifiy M., Banadaki Y. General spice models for memristor and application to circuit simulation of memristor-based synapses and memory cells. Journal of Circuits, Systems and Computers 2010, 19:407-424.
31. Shen Y., Wang J. An improved algebraic criterion for global exponential stability of recurrent neural networks with time-varying delays. IEEE Transactions on Neural Networks 2008, 19:528-531.
32. Smith L. Handbook of nature-inspired and innovative computing: integrating classical models with emerging technologies 2006, 433-475. Springer, New York.
33. Strukov D., Snider G., Stewart D., Williams R. The missing memristor found. Nature 2008, 453:80-83.
34. Takagi T., Sugeno M. Fuzzy identification of systems and its applications to modelling and control. IEEE Transactions on Systems, Man and Cybernetics 1985, SMC-15:116-132.
35. Wen S., Zeng Z. Dynamics analysis of a class of memristor-based recurrent networks with time-varying delays in the presence of strong external stimuli. Neural Processing Letters 2012, 35:47-59.
36. Wen S., Zeng Z., Huang T. Adaptive synchronization of memristor-based Chua's circuits. Physics Letters A 2012, 376:2775-2780.
37. Wen S., Zeng Z., Huang T. Dynamics behaviors of memristor-based delayed recurrent networks. Neural Computing and Applications 2012, 10.1007/s00521-012-0998-y.
38. Wu W., Cui B. Global robust exponential stability of delayed neural networks. Chaos, Solitons and Fractals 2008, 35:747-754.
39. Xing Z., Peng J. Exponential lag synchronization of fuzzy cellular neural networks with time-varying delays. Journal of the Franklin Institute 2012, 349:1074-1086.
40. Zeng Z., Wang J. Global exponential stability of recurrent neural networks with time-varying delays in the presence of strong external stimuli. Neural Networks 2006, 19:1528-1537.
41. Zeng Z., Wang J., Liao X. Global asymptotic stability and global exponential stability of neural networks with unbounded time-varying delays. IEEE Transactions on Circuits and Systems II 2005, 52:168-173.
42. Zhang G., Wang T., Li T., Fei S. Exponential synchronization for delayed chaotic neural networks with nonlinear hybrid coupling. Neurocomputing 2012, 85:53-61.
43. Zhao W., Tan Y. Harmless delay for global exponential stability of Cohen-Grossberg neural networks. Mathematics and Computers in Simulation 2007, 74:47-57.
44. Zhao W., Zhu Q. New results of global robust exponential stability of neural networks with delays. Nonlinear Analysis: Real World Applications 2010, 11:1190-1197.