On the optimal parameters of GMSSOR method for saddle point problems

For solving saddle point problems, SOR-type methods are investigated by many researchers in the literature. In this short note, we study the GMSSOR method for solving saddle point problems and obtain the optimal parameters which minimize the spectral (or pseudo-spectral) radii of the iteration matrices.     

Adaptive impulsive synchronization of uncertain delayed chaotic system with full unknown parameters via discrete‐time drive signals

This article investigates the adaptive impulsive synchronization of delayed chaotic system with full unknown parameters. Aiming at this problem, we propose a new adaptive strategy, in which both the adaptive–impulsive controller and the parameters adaptive laws are designed via the discrete‐time signals from the drive system. The corresponding theoretical proof is given to guarantee the effectiveness of the proposed strategy. Moreover, the concrete adaptive strategies are achieved for delayed Hopfield neural network, optical Ikeda system and the well‐known delayed Lü chaotic system. As expected, numerical simulations show the effectiveness of the proposed strategy. This method has potential applications in parameters estimation, secure communication, and cryptanalysis when only discrete signals are transmitted in communication channel. © 2014 Wiley Periodicals, Inc. Complexity 21: 43–51, 2016     

Robust stability analysis of stochastic neural networks with Markovian jumping parameters and probabilistic time‐varying delays

This article discusses the issue of robust stability analysis for a class of Markovian jumping stochastic neural networks (NNs) with probabilistic time‐varying delays. The jumping parameters are represented as a continuous‐time discrete‐state Markov chain. Using the stochastic stability theory, properties of Brownian motion, the information of probabilistic time‐varying delay, the generalized Ito's formula, and linear matrix inequality (LMI) technique, some novel sufficient conditions are obtained to guarantee the stochastical stability of the given NNs. In particular, the activation functions considered in this article are reasonably general in view of the fact that they may depend on Markovian jump parameters and they are more general than those usual Lipschitz conditions. The main features of this article are described in the following: first one is that, based on generalized Finsler lemma, some improved delay‐dependent stability criteria are established and the second one is that the nonlinear stochastic perturbation acting on the system satisfies a class of Lipschitz linear growth conditions. By resorting to the Lyapunov–Krasovskii stability theory and the stochastic analysis tools, sufficient stability conditions are established using an efficient LMI approach. Finally, two numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity 21: 59–72, 2016     

非单调带参数Perry-Shanno无记忆拟牛顿法的收敛性

给出了一种非单调带参数的Perry-Shanno无记忆拟牛顿法, 对于目标函数为凸函数, 在参数满足适当范围的情况下, 证明了算法的全局收敛性.     

多参数二次特征值问题重特征值的灵敏度分析

本文研究解析依赖于多参数的二次特征值问题重特征值的灵敏度分析,得到了重特征值的方向导数,证明了相应的特征向量矩阵和特征值平均值的解析性,给出了其一阶偏导数的表达式．然后以这些结论为基础,定义了二次特征值问题重特征值及其不变子空间的灵敏度,并给出了确定二次特征值问题所含矩阵中敏感元素的方法．     

标准体系的比例型寿命使用期模型与分析

本文在基于标准被废除按比例进行时的标准体系使用期的两个新模型。首先给出了模型假设条件,然后定义了标准使用期。根据假设给出了两个模型条件下的标准使用期公式,最后通过数值示例说明了标准使用期的公式使用。     

一个组合分布模型及其参数估计

本文根据极值分布理论,提出了一个由原始分布和尾分布组成的组合分布模型,研究了组合分布模型中原始分布和尾分布的确定方法,建立了组合分布模型参数估计的加权最优化模型,实例计算说明,组合分布较好地反映了风险变量极值事件的风险。     

Modified projective synchronization of uncertain fractional order hyperchaotic systems

Base on the stability theory of fractional order system, this work mainly investigates modified projective synchronization of two fractional order hyperchaotic systems with unknown parameters. A controller is designed for synchronization of two different fractional order hyperchaotic systems. The method is successfully applied to modified projective synchronization between fractional order Rössler hyperchaotic system and fractional order Chen hyperchaotic system, and numerical simulations illustrate the effectiveness of the obtained results.     

Sensitivity of a shallow-water model to parameters

An adjoint based technique is applied to a shallow water model in order to estimate the influence of the model’s parameters on the solution. Among parameters, the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients, Coriolis parameter and the amplitude of the wind stress tension are considered. Their influence is analyzed from three points of view:

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flexibility of the model with respect to a parameter that is related to the lowest value of the cost function that can be obtained in the data assimilation experiment that controls this parameter;

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possibility to improve the model by the parameter’s control, i.e., whether the solution with the optimal parameter remains close to observations after the end of control;

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sensitivity of the model solution to the parameter in a classical sense. That implies the analysis of the sensitivity estimates and their comparison with each other and with the local Lyapunov exponents that characterize the sensitivity of the model to initial conditions.

Two configurations have been analyzed: an academic case of the model in a square box and a more realistic case simulating Black sea currents. It is shown in both experiments that the boundary conditions near a rigid boundary highly influence the solution. This fact points out the necessity to identify optimal boundary approximation during a model development.     

一类正则化参数自由的线性约束凸优化问题的预测-校正算法

我们对文章的结构做这样的安排:第二节给出本文需要的预备知识;第三节简述单个目标函数问题(1.1)的己有算法和求解可能遇到的困难,第四节给出解决问题的预测-校正方法;第五节和第六节对问题(1.2)分别陈述己有方法的固有困难和我们提出的解决方案.最后,在第七节中,我们为提出的方法给出统一的算法框架,证明这类算法的收敛性和遍历意义下的收敛速率,同时给出我们的一些结论.