Dynamics of a Nonautonomous Plant Disease Model with General Nonlinear Incidence Rate and Time-Varying Impulse

In this paper, for controlling the spread of plant diseases, a nonautonomous SEIS (Susceptible → Exposed → Infectious → Susceptible) epidemic model with a general nonlinear incidence rate and time-varying impulsive control strategy is proposed and investigated. This novel model could result in an objective criterion on how to control plant disease transmission by replanting of healthy plants and removal of infected plants. Using the method of small amplitude perturbation, the sufficient conditions under which guarantee the globally attractive of the disease-free periodic solution and the permanence of the disease are obtained, that is, the disease dies out if R12>1.

Impulsive control of nonlinear systems with time-varying delays

A whole impulsive control scheme of nonlinear systems with time-varying delays, which is an extension for impulsive control of nonlinear systems without time delay, is presented in this paper. Utilizing the Lyapunov functions and the impulsive-type comparison principles, we establish a series of different conditions under which impulsively controlled nonlinear systems with time-varying delays are asymptotically stable. Then we estimate upper bounds of impulse interval and time-varying delays for asymptotically stable control. Finally a numerical example is given to illustrate the effectiveness of the method.

An improved impulsive control approach to nonlinear systems with time-varying delays

A scheme for the impulsive control of nonlinear systems with time-varying delays is investigated in this paper. Based on the Lyapunov-like stability theorem for impulsive functional differential equations （FDEs）, some sufficient conditions are presented to guarantee the uniform asymptotic stability of impulsively controlled nonlinear systems with time-varying delays. These conditions are more effective and less conservative than those obtained. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

Delay-dependent exponential stability of impulsive stochastic systems with time-varying delay

The problem of delay-dependent exponential stability is investigated for impulsive stochastic systems with time-varying delay. Although the exponential stability of impulsive stochastic delay systems has been discussed by several authors, few works have been done on delay-dependent exponential stability of impulsive stochastic delay systems. Firstly, the Lyapunov-Krasovskii functional method combing the free-weighting matrix approach is applied to investigate this problem. Some delay-dependent mean square exponential stability criteria are derived in terms of linear matrix inequalities. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive effects. The obtained results show that the system will stable if the impulses＇ frequency and amplitude are suitably related to the increase or decrease of the continuous flows, and impulses may be used as controllers to stabilize the underlying stochastic system. Numerical examples are given to show the effectiveness of the results.

New Results of Global Asymptotical Stability for Impulsive Hopfield Neural Networks with Leakage Time-Varying Delay

In this paper, Hopfield neural networks with impulse and leakage time-varying delay are considered. New sufficient conditions for global asymptotical stability of the equilibrium point are derived by using Lyapunov-Kravsovskii functional, model transformation and some analysis techniques. The criterion of stability depends on the impulse and the bounds of the leakage time-varying delay and its derivative, and is presented in terms of a linear matrix inequality (LMI).

Impulsive Synchronization of Nonlinear Stochastic Dynamical Networks with Time-Varying Delays

In this paper, an impulsive control strategy is proposed for a class of nonlinear stochastic dynamical networks with time-varying delay. Using the Lyapunov stability theory, a sufficient verifiable criterion for the exponential synchronization is derived analytically. Finally, a numerical simulation example is provided to verify the effectiveness of the proposed approach.

基于改进滑模观测器的PMSM无速传感控制设计

针对滑模观测器(SMO)因高频抖振导致电机转子速度和位置难以准确估计,且速度环PI控制器鲁棒性和速度跟踪性能较差的问题,提出一种基于改进滑模观测器的永磁同步电机(PMSM)无速传感控制设计.首先,在直接转矩控制系统中的滑模观测器后加入无限脉冲响应滤波器(IIR filter),以解决在滑模观测器输出中的高频噪声,并进一步采用连续的双曲正切函数代替不连续的符号函数,以改善系统抖振;其次,基于自抗扰控制器(ADRC)设计速度环,用以改善系统超调和转速之间的矛盾;最后,在Matlab/Simulink环境下搭建了硬件在环实验平台.仿真和结果表明,在相同负载和干扰条件下,相比传统无速度传感系统,本文所设计的自抗扰永磁同步电机无速传感控制能减小转速估计的抖振,且具有更优的鲁棒性和速度跟踪性能.

Set-Membership Filtering Subject to Impulsive Measurement Outliers:A Recursive Algorithm

This paper is concerned with the set-membership filtering problem for a class of linear time-varying systems with norm-bounded noises and impulsive measurement outliers.A new representation is proposed to model the measurement outlier by an impulsive signal whose minimum interval length(i.e.,the minimum duration between two adjacent impulsive signals)and minimum norm(i.e.,the minimum of the norms of all impulsive signals)are larger than certain thresholds that are adjustable according to engineering practice.In order to guarantee satisfactory filtering performance,a so-called parameter-dependent set-membership filter is put forward that is capable of generating a time-varying ellipsoidal region containing the true system state.First,a novel outlier detection strategy is developed,based on a dedicatedly constructed input-output model,to examine whether the received measurement is corrupted by an outlier.Then,through the outcome of the outlier detection,the gain matrix of the desired filter and the corresponding ellipsoidal region are calculated by solving two recursive difference equations.Furthermore,the ultimate boundedness issue on the time-varying ellipsoidal region is thoroughly investigated.Finally,a simulation example is provided to demonstrate the effectiveness of our proposed parameter-dependent set-membership filtering strategy.

Pinning impulsive synchronization of stochastic delayed coupled networks

In this paper, the pinning synchronization problem of stochastic delayed complex network （SDCN） is investigated by using a novel hybrid pinning controller. The proposed hybrid pinning controller is composed of adaptive controller and impulsive controller, where the two controllers are both added to a fraction of nodes in the network. Using the Lyapunov stability theory and the novel hybrid pinning controller, some sufficient conditions are derived for the exponential synchronization of such dynamical networks in mean square. Two numerical simulation examples are provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed control scheme has a fast convergence rate compared with the conventional adaptive pinning method.

Passivity Analysis of Impulsive Complex Networks

In this paper, we first investigate input passivity and output passivity for a class of impulsive complex networks with time-varying delays. By constructing suitable Lyapunov functionals, some input passivity and output passivity conditions are derived for the impulsive complex networks. Finally, an example is given to show the effectiveness of the proposed criteria.

Stochastic Modeling and Power Control of Time-Varying Wireless Communication Networks

Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.

基于深度学习算法的光通信系统信道均衡方法

为降低光通信系统的码间串扰和信号失真程度,提出基于深度学习算法的光通信系统信道均衡方法。建立光通信系统信道均衡模型,分析非线性失真、多径传输路径引发码间串扰问题,通过卷积循环神经网络信道均衡模型有效处理信道的非线性时变特性,降低码间串扰和信号失真,实现信道均衡。测试结果显示:在抽头数量比例为45%时,方法的误符号率均低于30.4%,交叉熵损失值均在0.035以下,应用性能良好;信道均衡后信号的星座图中,码间串扰和信号失真现象显著降低,应用性良好。

投资者情绪对中国IPO首日收益率影响的实证分析

以2009年1月～2014年3月上证交易数据为样本，利用主成分分析法构建基于中国国情的投资者情绪综合指数（ CICSI ），并采用VAR模型、格兰杰因果关系检验和脉冲响应等方法考查投资者情绪综合指数与中国IPO首日收益率之间的动态关系。结果表明，投资者情绪对IPO首日收益率有显著的正向影响；同时，IPO首日收益率的波动也会对投资者情绪波动有显著的冲击，但产生的影响在时间上会相对滞后。实证分析结果有助于了解投资者的行为特征、决策的过程及影响机制，对于投资者的管理与引导、定价效率的提高、相关机制的完善具有现实意义。

财政教育支出与经济增长关系的动态研究

2012年,我国财政性教育经费支出终于达到占GDP4%比重目标,这与国家多年来持续加大对教育的投入密切相关,也表明了国家对教育投入的重视。本文通过建立向量误差修正模型、Granger因果检验、脉冲响应函数以及方差分解方法实证分析财政教育支出与经济增长的动态关系。通过实证分析得到的主要结论:经济增长是引起财政教育支出增长的Granger原因,而固定资本增长是引起经济增长的Granger原因。经济增长对财政教育支出存在长期正向响应,而对固定资本的扰动是短期的响应;财政教育支出对经济增长的冲击贡献率持续增大,固定资本投资存在着短期的较好贡献,但长期影响小于财政教育支出的影响。

基于VAR模型的旅游发展、经济增长和碳排放的实证研究

利用1990~2014年中国旅游发展、经济增长和碳排放相关时间序列数据,建立相应的VAR(4)模型,通过协整检验、格兰杰因果关系检验、脉冲响应和方差分解分析,对三者之间的长期均衡关系及其动态性进行实证分析。研究结果表明:旅游发展、经济增长和碳排放之间存在长期均衡关系,且旅游业发展水平的上升对经济增长产生微弱的副作用,而经济增长促进旅游业发展,但尚处于"影响较弱"阶段,其作用有待加强;现阶段旅游发展对碳排放具有抑制作用,而碳排放在一定程度上阻碍了旅游业发展水平的提高;旅游发展、经济增长和碳排放变动的主要贡献因子均为其自身,且经济增长与碳排放二者间的相互影响具有非对称性,经济增长对碳排放的影响更大,而短期内碳排放对经济增长的影响较弱。

农业面源污染与经济增长的动态关系研究——基于1995—2011年福建省数据分析

运用计量经济模型中的协整检验、脉冲响应、方差分解工具,对福建省1995—2011年的农业面源污染与经济增长的关系进行实证研究。研究发现:农业面源污染中氮的产污量与人均GDP增长呈现"倒U型"的曲线关系;经济增长与农业面源污染中氮的产污量存在长期稳定的协整关系,即经济增长与农业面源污染存在长期的矛盾;人均实际GDP对农业面源污染的冲击是负向的,表明农业环境污染的加重制约了经济的可持续发展;方差分解显示人均GDP增长是解释农业面源污染方差变化的重要变量,而农业面源污染对经济增长方差变化的贡献度较小。最后在此基础上,提出有益于经济增长与农业环境保护协调发展的政策建议。

黑龙江省国有林区非木质林产品产业发展潜力研究——基于脉冲响应函数的分析

非木质林产品以其纯天然、来源可追溯、利用价值高等多重优势对实现林业经济转型有显著的提升作用。文章运用脉冲响应函数分析非木质林产品各产业对非木质林产品产业的动态影响效果,明确各产业发展潜力。结果表明:经济林产品的种植与采集、森林游憩服务为最具潜力产业,花卉种植与动物利用为短期潜力产业,非木质林产品加工制造业、林产化学产品制造与森林生产辅助服务为长期潜力产业,对非木质林产品产业发展起共同拉动作用。最后,针对研究结果给出若干促进非木质林产品产业发展的建议。

国际原油价格冲击对中国体育用品制造行业的影响

基于2003年1月～2011年4月的月度数据,通过引入VAR模型,构建了国际原油价格波动与体育用品制造行业发展、物价水平、货币供应量、实际有效汇率之间的动态关系系统,着重探讨了国际原油价格波动对我国体育用品制造行业及各宏观经济指标的影响。Granger因果关系分析表明,国际原油价格、物价水平、货币供应量和实际有效汇率彼此间存在单(双)向因果关系,且具有"传递效应",但与体育用品制造行业发展均不构成显著的Granger因果关联;VAR(1)建模结果发现,国际原油价格上涨不会使体育用品制造行业利润总额降低,仅放缓了增长速度;脉冲响应函数分析得出,国际原油价格波动对体育用品制造行业的短期影响比较显著,但长期效应不明显。方差分解结果显示,国际原油价格波动对体育用品制造行业的直接影响较小,但通过货币政策也可对其产生一定的间接影响,同时体育用品制造行业的发展状况也在一定程度上制约着货币政策的走势。

欠发达地区农业收益与农业从业人员动态变化——以江西省为例

运用E-G两步法协整检验、向量误差修正模型、格兰杰因果关系检验和脉冲响应函数在内的时间序列分析方法,对1984-2008年江西省农业收益与农业从业人员的动态关系进行计量分析。研究结果表明:农业从业率与农业贡献率之间存在长期稳定关系,农业贡献率与农业从业率之间存在着单向的格兰杰因果关系,农业贡献率变动显著地影响着实际农业就业率的变动,但农业从业率变动并不能显著地影响实际农业贡献率的变动。

中国居民消费与碳排放强度关系动态交互分析

基于1980-2010年的统计数据,构建居民消费水平和碳排放强度间的自相量回归模型,运用协整分析、脉冲响应函数和动态方差分解法,从不同视角对两组变量的动态交互响应关系进行研究分析,目的是为了解释我国居民消费水平和碳排放强度之间的内在联系、互动机制以及发展趋势。分析结果表明:尽管在短期内出现波动,我国居民消费水平和碳排放强度之间存在长期均衡关系;碳排放强度对居民消费的脉冲响应在短期内是正向加强的,此后逐渐减弱直至收敛。碳强度变化对居民消费水平的冲击具有明显的时效性和波动性;方差分解时序值显示,长期而言,碳排放强度对居民消费水平的影响较低且呈增长趋势,而居民消费水平对碳排放强度贡献度显著且增长迅速。