On delay-derivative-dependent stability of systems with fast-varying delays

Stability of linear systems with uncertain bounded time-varying delays is studied under the assumption that the nominal delay values are not equal to zero. An input-output approach to stability of such systems is known to be based on the bound of the L₂-norm of a certain integral operator. There exists a bound on this operator norm in two cases: in the case where the delay derivative is not greater than 1 and in the case without any constraints on the delay derivative. In the present note we fill the gap between the two cases by deriving a tight operator bound which is an increasing and continuous function of the delay derivative upper bound d?1. For d→∞ the new bound corresponds to the second case and improves the existing bound. As a result, for the first time, delay-derivative-dependent frequency domain and time domain stability criteria are derived for systems with the delay derivative greater than 1.     

Nonsmooth optimization for multiband frequency domain control design

Multiband frequency domain synthesis consists in the minimization of a finite family of closed-loop transfer functions on prescribed frequency intervals. This is an algorithmically difficult problem due to its inherent nonsmoothness and nonconvexity. We extend our previous work on nonsmooth H_∞ synthesis to develop a nonsmooth optimization technique to compute local solutions to multiband synthesis problems. The proposed method is shown to perform well on illustrative examples.     

基于人类视觉感知特性的一种纹理图象分割方法

在纹理图象分割的研究领域中,基于人类视觉感知特性的图象分割方法是一个重要的新方向,本文给出了一种纹理图象分割的方法,设计了一组参数不同的2D最佳正交极可分方向滤波器来提取图象特征,然后经过四叉树平滑,用模糊C－均值聚类对图象进行分类,最后进行边缘确定,实验结果表明,这种方法能获得较好的分割效果。     

A reactive GRASP and path relinking for a combined production–distribution problem

An NP-hard production–distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize total cost taking production setups, inventory levels and distribution into account. An integer linear model is proposed as a compact problem specification but it cannot be solved to optimality for large instances. Instead of using a classical two-phase approach (production planning and then route construction for each day), metaheuristics that simultaneously tackle production and routing decisions are developed: a GRASP (greedy randomized adaptive search procedure) and two improved versions using either a reactive mechanism or a path-relinking process. These algorithms are evaluated on 90 randomly generated instances with 50, 100 and 200 customers and 20 periods. The results confirm the interest of integrating production and distribution decisions, compared to classical two-phase methods. Moreover, reaction and path-relinking give better results than the GRASP alone.     

Limitations of nonlinear discrete periodic control for disturbance attenuation and robust stabilization

This paper presents a performance analysis of nonlinear periodically time-varying discrete controllers acting upon a linear time-invariant discrete plant. Time-invariant controllers are distinguished from strictly periodically time-varying controllers. For a given nonlinear periodic controller, a time-invariant controller is constructed. Necessary and sufficient conditions are given under which the time-invariant controller gives strictly better control performance than the time-invariant controller from which it was obtained, for the attenuation of l_p exogenous disturbances and the robust stabilization of l_p unstructured perturbations, for all p[1,∞].     

A method of predicting the number of clusters using Rand's statistic

Distributional and asymptotic results on the moment of Rand's C_k statistic were derived by DuBien and Warde [1981. Some distributional results concerning a comparative statistic used in cluster analysis. ASA Proceedings of the Social Statistics Section, 309–313.]. Based on those results, a method to predict the number of clusters is suggested by applying various agglomerative clustering algorithms. In the procedure, the methods using different indexes are examined and compared based on the concept of agreement (or, disagreement) between clusterings generated by different clustering algorithms on the set of data. Our method having practical generality works better than the other methods and assigns statistical meaning to C_k values in determining the number of clusters from the comparison.     

自组织RBF 神经网络对驾驶员主动安全性因素的辨识

利用自组织RBF神经网络对驾驶员主动安全性因素进行辨识。对网络进行训练时,首先由改进FCM算法根据输入样本内部关系确定RBF参数并通过一个聚类合理性聚类控制聚类个数,然后根据网络映射性能对RBF参数细调并对输出权值学习。利用本文给出的网络成功地对驾驶员的熟练程度进行了识别。     

Functional linear regression after spline transformation

Functional linear regression has been widely used to model the relationship between a scalar response and functional predictors. If the original data do not satisfy the linear assumption, an intuitive solution is to perform some transformation such that transformed data will be linearly related. The problem of finding such transformations has been rather neglected in the development of functional data analysis tools. In this paper, we consider transformation on the response variable in functional linear regression and propose a nonparametric transformation model in which we use spline functions to construct the transformation function. The functional regression coefficients are then estimated by an innovative procedure called mixed data canonical correlation analysis (MDCCA). MDCCA is analogous to the canonical correlation analysis between two multivariate samples, but is between a multivariate sample and a set of functional data. Here, we apply the MDCCA to the projection of the transformation function on the B-spline space and the functional predictors. We then show that our estimates agree with the regularized functional least squares estimate for the transformation model subject to a scale multiplication. The dimension of the space of spline transformations can be determined by a model selection principle. Typically, a very small number of B-spline knots is needed. Real and simulation data examples are further presented to demonstrate the value of this approach.     

黄河滩岸稳定性影响因素的敏感性分析

黄河滩岸的崩塌失稳将会对滩地和村庄造成严重冲蚀,甚至造成堤防冲决,对黄河滩岸稳定性及其影响因素的敏感性进行分析具有重要的工程实践意义.选择了影响滩岸稳定性较大的主要因素(土体凝聚力c、坡体内水头H和坡角α)进行分析.由c、H及α变化组成不同分析工况,采用边坡稳定性分析方法,分析了滩岸稳定性,并在此基础上研究了滩岸稳定性对c、H及α的敏感性.分析结果表明:在各种计算工况下,黄河滩岸是稳定的;c是影响滩岸坡体稳定性最强的因素,其敏感性随坡角及水头的增大而增强;H对滩岸坡体稳定性影响次之,其敏感性随坡角的增大而增大,随凝聚力的增大而减小;α对坡体稳定的敏感性相对较小,其随凝聚力的增大而减小,随水头的变化不明显.     

具有c1-可补子群的有限群结构分析

子群H在群G中被称为是c1-可补的(c1-supplemented),如果存在G的子群K使得G=HK且H∩T≤Z∞(G),其中Z∞(G)是G的超中心.本文研究素数幂阶子群的广义可补性对有限群结构的的影响,得到以下主要定理:对于G的任意Sylow p-子群P,如果P有子群D满足1<|D|<|P|且P每一个|D|阶及p|D|阶子群在G中均c1-可补,那么G超可解.该结果推广了一些已知的结果.