In this paper, we study the existence and stability of an equilibrium of discrete-time Cohen-Grossberg BAM Neural Networks with delays. We obtain several sufficient conditions ensuring the existence and stability of a...In this paper, we study the existence and stability of an equilibrium of discrete-time Cohen-Grossberg BAM Neural Networks with delays. We obtain several sufficient conditions ensuring the existence and stability of an equilibrium of such systems, using discrete Halanay-type inequality and vector Lyapunov methods. In addition, we show that the proposed sufficient condition is independent of the delay parameter. An example is given to demonstrate the effectiveness of the results obtained.展开更多
By using the continuation theorem of Mawhin＇s coincidence degree theory and the Liapunov func tional method, some sufficient conditions are obtained to ensure the existence, uniqueness and the global exponential stab...By using the continuation theorem of Mawhin＇s coincidence degree theory and the Liapunov func tional method, some sufficient conditions are obtained to ensure the existence, uniqueness and the global exponential stability of the periodic solution to the BAM-type Cohen-Grossberg neural networks involving timevarying delays.展开更多
基金supported by the National Natural Science Foundation of P.R.China(60764003)the Natural Science Foundation of Xinjiang(2010211A07)the Scientific Research Programmes of Colleges in Xinjiang(XJEDU2007G01)
基金supported by the Natural Science Foundation of Fujian Province (No.S0750008)the National Natural Science Foundation of China (No.10432010).
文摘In this paper, we study the existence and stability of an equilibrium of discrete-time Cohen-Grossberg BAM Neural Networks with delays. We obtain several sufficient conditions ensuring the existence and stability of an equilibrium of such systems, using discrete Halanay-type inequality and vector Lyapunov methods. In addition, we show that the proposed sufficient condition is independent of the delay parameter. An example is given to demonstrate the effectiveness of the results obtained.
基金Supported by the National Natural Science Foundation of China (No. 10971173)the Scientific Research Foundation of Hunan Provincial Educational Department (No. 05A057)+1 种基金supported by the Aid Program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Provincethe Construct Program of the Key Discipline in Hunan Province
文摘By using the continuation theorem of Mawhin＇s coincidence degree theory and the Liapunov func tional method, some sufficient conditions are obtained to ensure the existence, uniqueness and the global exponential stability of the periodic solution to the BAM-type Cohen-Grossberg neural networks involving timevarying delays.
