Stability Analysis of Stochastic Swarm Systems

In this paper,we present a model of stochastic swarm system and prove the stability of this kind of systems. We establish the stable aggregating behavior for the group using a coordination control scheme. This individual-based control scheme is a combination of attractive and repulsive interactions among the individuals in the group,which ensures the cohesion of the group and collision avoidance among the individuals. The dynamics of each individual depends on the relative positions between the individuals and the influences of the random disturbances. Under the influences of the noises,this position-based control strategy still generates the stable aggregating behavior harmoniously for the group and the self-organized swarm pattern is formed.     

Convergence of Recursive Identification for ARMAX Process with Increasing Variances

The autoregressive moving average exogenous (ARMAX) model is commonly adopted for describing linear stochastic systems driven by colored noise. The model is a finite mixture with the ARMA component and external inputs. In this paper we focus on a parameter estimate of the ARMAX model. Classical modeling methods are usually based on the assumption that the driven noise in the moving average (MA) part has bounded variances, while in the model considered here the variances of noise may increase by a power of log n. The plant parameters are identified by the recursive stochastic gradient algorithm. The diminishing excitation technique and some results of martingale difference theory are adopted in order to prove the convergence of the identification. Finally, some simulations are given to show the reliability of the theoretical results.     

Discrete Time Optimal Adaptive Control for Linear Stochastic Systems

The least-squares (LS) algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares (WLS) algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for adaptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller, this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.     

带有双障碍的反射倒向随机微分方程的逆比较定理

讨论了带有双障碍的反射倒向随机微分方程的逆比较问题，在适当的条件下建立了几个关于其生成元的逆比较定理.     

关于非频带有限随机信号的采样级数的逼近

香农采样定理可以恢复确定性频带有限信号.而真实信号经常是非频带有限的,这类信号可以被看作边带趋于无穷的频带有限信号.除了确定性型号,平稳的随机信号在许多领域发挥了重要作用.为了解决非频带有限的平稳过程的采样问题,借助香农采样定理,获得当功率在频域衰减时该类信号的采样级数,并求得该级数分别满足均方收敛和以概率1收敛的条件.     

基于无容量限制的p-枢纽中位问题的随机优化

在枢纽网络设计时, 未来的成本和需求等参数具有不确定性. 为了使设计的网络能在各种情景下具有最优的期望成本, 提出了无容量限制的多分配严格p-枢纽中位随机优化模型. 考虑到模型本身的结构特点和复杂程度, 采用了PH分解算法结合增广拉格朗日松弛算法, 将原问题转化为若干个独立子问题来求解. 使用了基于经典算例的随机数据集合对模型和算法进行了测试, 算例结果表明尤其在情景数量较大的情况下, 算法体现出较高的效率. 同时, 通过随机解价值分析了使用随机优化模型对于该算例的意义.     

DWT和DCT相结合的水印算法

提出了一种基于余弦和小波变换相结合的水印嵌入方案.对水印图像进行二次置乱加密,再将一次小波分解,将得到的逼近系数和细节系数分别转换为一维序列,并量化组合生成待嵌入的二进制数据流.根据宿主图像的纹理、亮度特征将作离散余弦变换后的原图像分类,对不同的类采用不同的量化因子修改DCT系数矩阵从而实现水印的嵌入,水印检测过程不需要宿主图像的参与.实验表明该算法不仅具有良好的不可见性,而且在经过JPEG压缩、剪切、缩放、噪声添加及轻微几何变形等常见图像处理后,仍能正确提取出水印图像,水印图像压缩对码率的影响较小,适合网络传输.     

两参数跳型随机微分方程解的存在性和唯一性

通过逐次逼近方法，讨论了由Ｐｏｉｓｓｏｎ过程驱动的随机微分方程，在系数满足非Ｌｉｐｓｃｌｈｔｚ条件下，得到非齐次强解的存在性和唯一性。     

Markov调制的随机微分方程极小解与极大解的存在性

运用比较方法,在较为一般的条件下,证明了一维M arkov调制的随机微分方程极小解与极大解的存在性。     

New criteria on delayed state feedback stabilization for stochastic systems with time-varying delay

The problems of robust exponential stability in mean square and delayed state feedback stabilization for uncertain stochastic systems with time-varying delay are studied.By using Jensen’s integral inequality and combining with the free weighting matrix approach,new delay-dependent stability conditions and delayed state feedback stabilization criteria are obtained in terms of linear matrix inequalities.Meanwhile,the proposed delayed state feedback stabilization criteria are more convenient in application than the existing ones since fewer tuning parameters are involved.Numerical examples are given to illustrate the effectiveness of the proposed methods.