This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point,...This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov-Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result.展开更多
The problem of partial stability is investigated for a class of continuous-time large-scale systems. Under assumption that the null solution of the isolated subsystems is stable, based on decomposition-aggregation met...The problem of partial stability is investigated for a class of continuous-time large-scale systems. Under assumption that the null solution of the isolated subsystems is stable, based on decomposition-aggregation methods and Lyapunov second method, some theorems concerning the globally partial asymptotic stability and globally partial exponential stability are obtained via utilizing the inequality analysis technique and comparison technique. Finally, an example is presented to illustrate the results.展开更多
In this paper, a new sufficient condition for the global exponential stability of a unique equilibrium point of discrete-time cellular neural networks is given. It is shown that the condition relies on the feedback ma...In this paper, a new sufficient condition for the global exponential stability of a unique equilibrium point of discrete-time cellular neural networks is given. It is shown that the condition relies on the feedback matrices and is independent of the delay parameter. Furthermore, this condition is less restrictive than those given in the literature.展开更多
Necessary conditions for the exponential stability of the linear discrete time-delay systems are presented by employing the so-called Lyapunov–Krasovskii functional approach.These conditions not only provide a new to...Necessary conditions for the exponential stability of the linear discrete time-delay systems are presented by employing the so-called Lyapunov–Krasovskii functional approach.These conditions not only provide a new tool for stability analysis of the linear discrete timedelay system by characterising instability domains,but also extend the existing results of the linear discrete time-delay system.Simultaneously,we investigate several crucial properties that connect the Lyapunov matrix and the fundamental matrix of the system.Finally,the robust stability analysis of the linear discrete time-delay systems with norm-bounded uncertainties is presented.Numerical examples illustrate the validity of the obtained results.展开更多
Discrete-time version of the bi-directional Cohen-Grossberg neural network is stud-ied in this paper. Some sufficient conditions are obtained to ensure the global exponen-tial stability of such networks with discrete ...Discrete-time version of the bi-directional Cohen-Grossberg neural network is stud-ied in this paper. Some sufficient conditions are obtained to ensure the global exponen-tial stability of such networks with discrete time based on Lyapunov method. These results do not require the symmetry of the connection matrix and the monotonicity, boundedness and differentiability of the activation function.展开更多
基金Project supported by the National Natural Science Foundations of China(Grant No.70871056)the Society Science Foundation from Ministry of Education of China(Grant No.08JA790057)the Advanced Talents'Foundation and Student's Foundation of Jiangsu University,China(Grant Nos.07JDG054 and 07A075)
文摘This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov-Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result.
文摘The problem of partial stability is investigated for a class of continuous-time large-scale systems. Under assumption that the null solution of the isolated subsystems is stable, based on decomposition-aggregation methods and Lyapunov second method, some theorems concerning the globally partial asymptotic stability and globally partial exponential stability are obtained via utilizing the inequality analysis technique and comparison technique. Finally, an example is presented to illustrate the results.
基金The work is supported by Scientific Research Fund of Hunan Provincial Education Department (03C248).
文摘In this paper, a new sufficient condition for the global exponential stability of a unique equilibrium point of discrete-time cellular neural networks is given. It is shown that the condition relies on the feedback matrices and is independent of the delay parameter. Furthermore, this condition is less restrictive than those given in the literature.
基金This work was partially supported by the National Natural Science Foundation of China(11371006 and 61703148)the Basic Research Operating Expenses Program of Colleges and Universities in Heilongjiang Province(HDJCCX-2016212 and RCCX201717)+1 种基金the Natural Science Foundation of Heilongjiang Province(QC2018083)the Heilongjiang University Innovation Fund for Graduates(YJSCX2018-057HLJU).
文摘Necessary conditions for the exponential stability of the linear discrete time-delay systems are presented by employing the so-called Lyapunov–Krasovskii functional approach.These conditions not only provide a new tool for stability analysis of the linear discrete timedelay system by characterising instability domains,but also extend the existing results of the linear discrete time-delay system.Simultaneously,we investigate several crucial properties that connect the Lyapunov matrix and the fundamental matrix of the system.Finally,the robust stability analysis of the linear discrete time-delay systems with norm-bounded uncertainties is presented.Numerical examples illustrate the validity of the obtained results.
基金supported by Scientific Research Foundation of Hunan Provincial EducationDepartment (04A055, 05A057,03C009)
文摘Discrete-time version of the bi-directional Cohen-Grossberg neural network is stud-ied in this paper. Some sufficient conditions are obtained to ensure the global exponen-tial stability of such networks with discrete time based on Lyapunov method. These results do not require the symmetry of the connection matrix and the monotonicity, boundedness and differentiability of the activation function.
基金Supported by National Natural Science Foundation of China(11471071)Natural Science Fundation of Shanghai(14ZR1401200)+1 种基金Shanghai Pujiang Program(16PJ1408000)Natural Science Fund of Shanghai Normal University(SK201603)
