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The dynamic stability of this system is discussed by the Hopf bifurcation theory and the condition of the limit cycle occurring is given.

应用Hopf分岔理论讨论了时滞动力系统动态稳定性,给出了系统产生极限环的条件,最后用数值模拟的方法研究了时滞参数对系统极限环幅值的影响。

A novel neural network model, named delayed standard neural network model, is proposed, which is the interconnection of a linear dynamic system and a bounded static delayed nonlinear operator.

摘要提出一种新的神经网络模型---时滞标准神经网络模型,它由线性动力学系统和有界静态时滞非线性算子连接而成。

Fault tolerant control problems of two class interval systems are presented.

3针对无时滞和带有时滞的两类区间系统,给出了各自的容错控制器设计方法。

In Chapter 2,we deal with the robust stability and stabilization problems for a class of stochastic time-delay interval uncertain systems with nonlinear dis-turbances by developing delay-dependent analysis techniques,where the It?

第二章通过发展一个时滞依赖分析技巧,讨论了一类带有非线性干扰和区间不确定参数的随机时滞系统的鲁棒镇定问题。

The problem of guaranteed cost control via memoryless state feedback is addressed for a class of interval singular systems with delayed state.

针对一类具有状态时滞时滞区间广义系统,基于状态反馈研究了保性能控制问题。

The problem of absolute stability of Lurie nonlinear systems with time-delay is investigated by using aug-mented Lyapunov functional combined with the free-weighting matrix approach.

利用增广的Lyapunov泛函结合自由权矩阵方法,对非线性Lurie时滞系统的绝对稳定性问题进行了研究,得到了系统基于线性矩阵不等式的具有更低保守性的时滞相关绝对稳定条件。

When the parameters of complex system are variable by time, it is more difficult to design the control system.

时滞特性是工业生产过程中普遍存在的现象,由于时滞现象的存在,扰动不能被及时察觉,控制作用需长时间后才能反映到系统输出上,因此使控制器参数不易选取,若控制参数调整不当,会造成系统控制品质的下降,严重时会导致系统不稳定。

These results include several sufficient conditions for the global exponential stability of general neural networks with time-varying delays and without monotone, bounded, or continuously differentiable activation function.

不同于已有文献用Liapunov函数或泛函法研究稳定性问题时,将时滞项作为干扰处理的方法,给出了利用时滞项让系统稳定的结果。

A sufficient condition is obtained to ensure the existence and uniqueness of almost periodic solution for MAM neural network with time-varying delays by way of exponential dichotomy and contraction map theorem. Moreover, the global exponential stability of the almost periodic solution for this type of MAM neural network is proved by using Halanay inequality.

利用指数二分法结合运用压缩映射原理获得了变时滞多向联想记忆神经网络模型概周期解的唯一存在性,利用Halanay不等式证明了变时滞多向联想记忆神经网络概周期解的全局指数稳定性。

A convex combination condition and a switching strategy are derived.

针对离散单时滞切换系统,提出了一个使系统渐近稳定的充分性条件,给出了该系统的无记忆状态反馈镇定和无记忆输出反馈镇定,并将结果推广到不确定离散时滞切换系统的鲁棒镇定。

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