Existence and stability of almost periodic solutions of Hopfield neural networks with continuously distributed delays

In this paper, the global stability and almost periodicity are investigated for Hopfield neural networks with continuously distributed neutral delays. Some sufficient conditions are obtained for the existence and globally exponential stability of almost periodic solution by employing fixed point theorem and differential inequality techniques. The results of this paper are new and they complement the previously known ones. Finally, an example is given to demonstrate the effectiveness of our results.     

Poisson stable motions of monotone nonautonomous dynamical systems

In this paper, we study the Poisson stability(in particular, stationarity, periodicity, quasiperiodicity, Bohr almost periodicity, almost automorphy, recurrence in the sense of Birkhoff, Levitan almost periodicity, pseudo periodicity, almost recurrence in the sense of Bebutov, pseudo recurrence, Poisson stability) of motions for monotone nonautonomous dynamical systems and of solutions for some classes of monotone nonautonomous evolution equations(ODEs, FDEs and parabolic PDEs). As a byproduct, some of our results indicate that all the trajectories of monotone systems converge to the above mentioned Poisson stable trajectories under some suitable conditions, which is interesting in its own right for monotone dynamics.     

Periodicity hubs and wide spirals in a two-component autonomous electronic circuit

We report an autonomous circuit containing periodicity hubs with surprisingly broad spirals. Knowledge of broad spirals is important because all presently known spirals are compressed along specific directions in parameter space making them difficult to study experimentally and theoretically. We characterize the performance of the circuit by computing stability diagrams for relevant sections of the control space. In addition, the alternation of chaotic and periodic spiral phases is contrasted with equivalent alternations obtained from an experimental implementation of the circuit.     

Exponential stability and periodicity of cellular neural networks with time delay

This paper investigates the problem of exponential stability and periodicity for a class of delayed cellular neural networks (DCNN’s). By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via constructing Lyapunov functional. Those conditions suitable are associated with some initial value and are represented by some blocks of the interconnection matrix. Two examples are discussed to illustrate the main results.     

Stability Properties and Nonlinear Mappings of Two and Three-Layer Stratified Flows

Two and three-layer models of stratified flows in hydrostatic balance are studied. For the former, nonlinear transformations are found that map [ baroclinic ] two-layer flows with either rigid top and bottom lids or vertical periodicity, into [ barotropic ] single-layer, shallow water free-surface flows. We have previously shown that two-layer flows with Richardson number greater than one are nonlinearly stable, in the following sense: when the system is well-posed at a given time, it remains well-posed through the nonlinear evolution. Here, we give a general necessary condition for the nonlinear stability of systems of mixed type. For three-layer flows with vertical periodicity, the domains of local stability are determined and the system is shown not to satisfy the necessary condition for nonlinear stability. This means that there are wave-motions that evolve into shear unstable flows.     

Rich dynamic of a stage-structured prey–predator model with cannibalism and periodic attacking rate

The dynamic behavior of a stage-structure prey–predator model with cannibalism for prey and periodic attacking rate for predator is investigated. Firstly, the permanence, locally and globally asymptotic stability analyses of the model with constant attacking rate are explored. After that, sufficient conditions for the permanence of the corresponding nonautonomous system with periodic attacking rate are obtained. Furthermore, numerical simulations are presented to illustrate the effects of periodic attacking rate. Simulation results show that the system with periodic attacking rate shows a rich behaviors, including period-doubling and period-having bifurcations, chaos and windows of periodicity.     

Stationary solutions to phase field crystal equations

This paper is devoted to the analytical and numerical study of stationary solutions of the one‐dimensional Phase Field Crystal Equation. This new model recently introduced by K. Elder and M. Grant describes phase transformations at the atomic level on large time scales. By using bifurcation methods, we investigate the quantitative and qualitative properties of these solutions: multiplicity, stability, and periodicity. Quite unusual bifurcation diagrams are obtained by numerical simulations. Copyright © 2010 John Wiley & Sons, Ltd.     

数理金融模型中Abel方程与Bernoulli方程周期问题的等价性

近年来随机微分方程在数理金融中的应用越来越得到人们的重视,而微分方程的周期性研究对经济模型也越来越重要,Abel(阿贝尔)、Bernoulli(伯努利)方程的周期性具有一定的指导性,但周期性问题的研究常具有一定的难度,为了解决这个问题,采用Mironenko发明的反射函数理论,通过构造与Abel方程、Bernoulli方程共同特征的更一般的方程,得到它们的反射函数,研究了Abel方程与Bernoulli方程的等价性,通过Poincare映射得出了它们相同的周期解问题.     

Global exponential stability and periodicity of reaction–diffusion recurrent neural networks with distributed delays and Dirichlet boundary conditions

In this paper, global exponential stability and periodicity of a class of reaction–diffusion recurrent neural networks with distributed delays and Dirichlet boundary conditions are studied by constructing suitable Lyapunov functionals and utilizing some inequality techniques. We first prove global exponential convergence to 0 of the difference between any two solutions of the original neural networks, the existence and uniqueness of equilibrium is the direct results of this procedure. This approach is different from the usually used one where the existence, uniqueness of equilibrium and stability are proved in two separate steps. Secondly, we prove periodicity. Sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the equilibrium and periodic solution are given. These conditions are easy to verify and our results play an important role in the design and application of globally exponentially stable neural circuits and periodic oscillatory neural circuits.     

On the global periodicity of discrete dynamical systems and application to rational difference equations

A new necessary condition for global periodicity of discrete dynamical systems and of difference equations is obtained here. This condition will be applied to contribute to solving the problem of global periodicity for second order rational difference equations.     

变时滞Hopfield神经网络的周期解存在性及其全局指数稳定性

利用拓扑度理论中的连续性引理和推广Halanay不等式研究了变时滞的细胞神经网络的周期解的存在性及全局指数稳定性.给出了判别周期解及指数稳定性的代数判据,所得判据易于检验,具有广泛的实用性．同时,改进了已有文献的相关结论,最后通过数值例子说明结论的有效性．     

Stability and almost periodicity of asymptotically dominated semigroups of positive operators

We discuss conditions such that strong stability and strong asymptotic compactness of a (discrete or continuous) semiflow defined on a subset in the positive cone of an ordered Banach space is preserved under asymptotic domination. This is used to show that on a Banach lattice with order continuous norm strong stability and almost periodicity of a (discrete or strongly continuous) semigroup of positive operators is preserved under asymptotic domination.

     

Nonlinear temporal dynamics in magnetic fluids between undulatory parallel walls

The effects of undulatory parallel walls and a normal magnetic field on the stability of weakly nonlinear waves at a horizontal interface of two magnetic inviscid fluids are investigated. We assumed that the walls have a weak sinusoidal undulation. The frequency of the main waves is similar to a problem having smooth boundaries. The breaker surface tension and the breaker magnetic field are obtained. The stability analysis concerns the interaction of two propagation wave numbers satisfying the resonance condition imposed by the periodicity of the sinusoidal walls. The first-resonance case occurs whenever the wall wave number is nearly equal to twice the propagation wave number while the second-resonance case occurs whenever the two kinds of wave numbers are nearly equal. When the wave number of the undulation is far from the propagation wave number, the sinusoidal walls have the same effect of the smooth walls on the stability criterion. The stability conditions and the transition curves in the two resonance cases are treated away from the critical state. The existence conditions and stability of Stokes waves near the critical state are discussed. Numerous illustrations and graphs amplify the work.     

最小偏差分析法在经济周期分析中的应用

利用最小偏差分析法,分析了我国GDP增长率的周期性特征,并对我国今后几年的GDP增长率进行了预测.分析的结果是:从1953—2006年,我国GDP增长率存在着7年左右的小周期,15年左右的中周期,19年左右的中长周期和28年左右的大周期,而且随着时间的推移,经济周期的波动幅度逐渐趋小,反映出经济增长的稳定性增强.预测的结果是:今后几年(2年或更长一段时间)我国GDP增长率应该保持在10%左右,波动的区间为[9%,11%].     

Periodic strongly continuous semigroups

Summary It is shown that three possible definitions of periodicity of a strongly continuous semigroup are equivalent. A complete characterization of periodicity is obtained in terms of the infinitesimal generator. An example is given to illustrate how the results tie in with the classical theory of periodic continuous functions. Finally some results are obtained for the case when the underlying space is a Hilbert space. Entrata in Redazione il 20 ottobre 1976. The research for this paper was done while the author was supported by the Netherlands Organization for the Advancement of Pure Research (Z.W.O.).     

Dynamical behaviors of fuzzy reaction–diffusion periodic cellular neural networks with variable coefficients and delays

When modeling neural networks in a real world, not only diffusion effect and fuzziness cannot be avoided, but also self-inhibitions, interconnection weights, and inputs should vary as time varies. In this paper, we discuss the dynamical behaviors of delayed reaction–diffusion fuzzy cellular neural networks with varying periodic self-inhibitions, interconnection weights as well as inputs. By using Halanay’s delay differential inequality, M$M$-matrix theory and analytic methods, some new sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential stability of the periodic solution, and the exponentially convergent rate index is also estimated. In particular, the traditional assumption on the differentiability of the time-varying delays is no longer needed. The methodology developed in this paper is shown to be simple and effective for the exponential periodicity and stability analysis of neural networks with time-varying delays. Two examples are given to show the usefulness of the obtained results that are less restrictive than recently known criteria.     

Intervals of periodicity and absolute stability of explicit nyström methods fory″=f(x,y)

We examine intervals of periodicity and absolute stability of explicit Nyström methods fory=f(x,y) by applying these methods to the test equationy=– ² y,>0. We consider in detail general families of fourth-order explicit Nyström methods; necessary and sufficient conditions are given to characterize methods which possess non-vanishing intervals of periodicity and absolute stability. We establish closed-form expressions giving intervals of periodicity and/or absolute stability, in case these exist, for any fourth-order method. We then show that the methodM ₄ (1/6, 5/6) has the largest interval of periodicity out of all fourth-order methods; we also obtain the fourth-order method with the largest interval of absolute stability. The corresponding results for second and third-order explicit Nyström methods are also included.     

Stability and periodicity in delayed cellular neural networks with impulsive effects

In the paper, the global exponential stability and periodicity are investigated for delayed cellular neural networks with impulsive effects. Some sufficient conditions are derived for checking the global exponential stability and the existence of periodic solution for this system based on Halanay inequality, mathematical induction and fixed point theorem. The criteria given are easily verifiable, possess many adjustable parameters, and depend on impulses, which provides flexibility for the design and analysis of delayed cellular neural networks with impulses.     

DYNAMICS OF NEW CLASS OF HOPFIELD NEURAL NETWORKS WITH TIME-VARYING AND DISTRIBUTED DELAYS

In this paper,we investigate the dynamics and the global exponential stability of a new class of Hopfield neural network with time-varying and distributed delays.In fact,the properties of norms and the contraction principle are adjusted to ensure the existence as well as the uniqueness of the pseudo almost periodic solution,which is also its derivative pseudo almost periodic.This results are without resorting to the theory of exponential dichotomy.Furthermore,by employing the suitable Lyapunov function,some delay-independent sufficient conditions are derived for exponential convergence.The main originality lies in the fact that spaces considered in this paper generalize the notion of periodicity and almost periodicity.Lastly,two examples are given to demonstrate the validity of the proposed theoretical results.     

一类具密度制约SIS模型的全局稳定性和周期性

研究了一类具密度制约和双线性传染率的S IS传染病模型,考虑到了实际中对易感者和传染者的控制,得到了地方病平衡点的全局渐近稳定性和系统的周期性,并给出了生物学解释和仿真.