Efficient estimation of seemingly unrelated additive nonparametric regression models

This paper is concerned with the estimating problem of seemingly unrelated (SU) nonparametric additive regression models. A polynomial spline based two-stage efficient approach is proposed to estimate the nonparametric components, which takes both of the additive structure and correlation between equations into account. The asymptotic normality of the derived estimators are establishedi. The authors also show they own some advantages, including they are asymptotically more efficient than those based on only the individual regression equation and have an oracle property, which is the asymptotic distribution of each additive component is the same as it would be if the other components were known with certainty. Some simulation studies are conducted to illustrate the finite sample performance of the proposed procedure. Applying the proposed procedure to a real data set is also made.     

Stability analysis of cellular neural networks with time-varying delay

The global asymptotic stability of cellular neural networks with delays is investigated. Three kinds of time delays have been considered. New delay-dependent stability criteria are proposed and are formulated as the feasibility of some linear matrix inequalities, which can be checked easily by resorting to the recently developed interior-point algorithms. Based on the Finsler Lemma, it is theoretically proved that the proposed stability criteria are less conservative than some existing results.     

基于LMI的连续时间模糊大系统的分散镇定

讨论了连续时间模糊大系统的分散镇定问题。整个模糊大系统由m个相互关联的T-S子模糊系统组成。基于李亚普诺夫稳定性理论及大系统分散控制理论,将单个模糊系统的稳定性条件推广到关联模糊大系统的情形,给出了保证该模糊大系统闭环渐近稳定的分散化并行分布补偿(decentralizedparalleldistributedcompensation,DPDC)控制器的设计方法。这些分散控制器的存在条件均以LMI的形式出现,因此可通过Matlab的LMI工具箱有效地对其进行求解。仿真例子说明了所提方法的有效性。     

Adjusted Empirical Likelihood Estimation of Distribution Function and Quantile with Nonignorable Missing Data

This paper considers the estimation problem of distribution functions and quantiles with nonignorable missing response data. Three approaches are developed to estimate distribution functions and quantiles, i.e., the Horvtiz-Thompson-type method, regression imputation method and augmented inverse probability weighted approach. The propensity score is specified by a semiparametric exponential tilting model. To estimate the tilting parameter in the propensity score, the authors propose an adjusted empirical likelihood method to deal with the over-identified system. Under some regular conditions, the authors investigate the asymptotic properties of the proposed three estimators for distribution functions and quantiles, and find that these estimators have the same asymptotic variance. The jackknife method is employed to consistently estimate the asymptotic variances. Simulation studies are conducted to investigate the finite sample performance of the proposed methodologies.     

Positivity and Stability of Fractional-Order Linear Time-Delay Systems

This article focuses on the positivity and the asymptotic stability of fractional-order linear time-delay systems (FOLTDSs) which are composed of N (N ≥ 2) subsystems. Firstly, a sufficient and necessary condition is given to ensure the positivity of FOLTDSs. The solutions of the studied systems are obtained by using the Laplace transform method, and it can be observed that the positivity of FOLTDSs is completely determined by the series of matrices and independent of the magnitude of time-delays. Secondly, a theorem is given to prove the asymptotic stability of positive FOLTDSs. By considering the monotonicity and asymptotic properties of systems with constant time-delay, it is further shown that the asymptotic stability of positive FOLTDSs is independent of the time-delay. Next, a state-feedback controller, whose gain matrix is derived by resolving a linear programming question, is designed such that the state variables of the systems are nonnegative and asymptotically convergent. When the order of the FOLTDSs is greater than one, by utilizing a proposed property of Caputo derivative, a sufficient condition for the positivity of FOLTDS is presented. Finally, simulation examples are presented to verify the validity and practicability of the theoretical analysis.

     

Stability analysis of extended discrete-time BAMneural networks based on LMI approach

1 .INTRODUCTIONBidirectional associative memory model is a kind ofneural network models in common use with the abili-ty of information memory and association. Since thedistributed memory of the information,the networkcan associate a completed and clear mode stored in itfroman uncompleted and fuzzy mode . Bidirectionalassociative memory (BAM) proposed by B. KoskoinRef .[1] is a generalization of Cohen-Grossberg’smodel from single layer to two layers . Since then,there have beenlots of …     

CONFIDENCE LOWER LIMITS FOR RESPONSE PROBABILITIES UNDER THE LOGISTIC RESPONSE MODEL

The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach. The high order approximation to the conditional distribution of a statistic for an interested parameter and then the lower confidence limits of response probabilities are derived. A simulation comparing these lower confidence limits with those obtained from the asymptotic normality is conducted. The proposed approximation is applied to two real data sets. Numerical results show that the saddlepoint approximations are much more accurate than the asymptotic normality approximations, especially for the cases of small or moderate sample sizes.     

通信受限不确定Delta算子网络系统H∞滤波

研究了一类基于Delta算子的通信受限条件下参数不确定网络系统H∞滤波问题。在通信受限条件下,采用通信序列对网络控制系统进行分析,构建Delta算子描述的不确定系统滤波误差模型。利用线性矩阵不等式和Lyapunov-Krasovskii泛函提出滤波误差系统渐近稳定的充分条件,证明了系统的H∞性能,并给出滤波器的设计方法。数值仿真结果验证了所提方法的有效性。     

Regression Function Comparison for Paired Data

In this paper, the regression function comparison for paired data is studied. The proposed test statistic is based on the weighted integral of characteristic function marked by the difference of responses. There are several merits of the proposed statistic. For instance, it takes a simple V-statistic form. No bandwidth is needed. No moment conditions are required for covariates. It can be applied to covariates of any fixed dimension. The asymptotic results are also developed. It is proven that n times the proposed test statistic converges to a finite limit under the null hypothesis and the test is consistent against any fixed alternatives. Local alternative hypotheses which converge to the null hypothesis at the rate of n-1/2 are also detected. A suitable Bootstrap algorithm is also proposed for the implementation of the proposed test statistic. Simulation studies are carried out to illustrate the merits of the proposed method. A real data example is also used to illustrate the proposed testing procedures.     

Single-Index Quantile Regression with Left Truncated Data

The purpose of this paper is two fold. First, the authors investigate quantile regression (QR) estimation for single-index QR models when the response is subject to random left truncation. The random weights are introduced to deal with left truncated data and the associated iteration estimation method is proposed. The asymptotic properties for the proposed QR estimates of the index parameter and unknown link function are both obtained. Further, by combining the QR loss function and the adaptive LASSO penalization, a variable selection procedure for the index parameter is introduced and its oracle property is established. Second, a weighted empirical log-likelihood ratio of the index parameter based on the QR method is introduced and is proved to be asymptotic standard chi-square distribution. Furthermore, confidence regions of the index parameter can be constructed. The finite sample performance of the proposed methods are demonstrated. A real data analysis is also conducted to show the usefulness of the proposed approaches.

     

Razumikhin-type theorems for asymptotic stability of impulsive stochastic functional differential systems

<正>In this paper,we investigate the pth moment uniformly asymptotic stability of impulsive stochastic functional differential systems by extending some Razumikhin-type theorems.Based on the Lyapunov functions and Razumikhin techniques,some criteria are established and their applications to impulsive stochastic delay systems are proposed.An illustrative example shows the effectiveness of our results.     

目标轨线迭代可变的非线性系统自适应学习控制

针对含有混合参数的非线性不确定系统,提出了一种自适应迭代学习控制方案。该方案利用Back-stepping方法和参数重组技巧相结合,可以处理目标轨线迭代可变的跟踪问题。通过引入微分-差分自适应学习律,设计了一种自适应控制策略,使得跟踪误差在一个有限区间上的积分渐近收敛于零;通过构造Lyapunov-like函数,给出了闭环系统收敛的一个充分条件。数值仿真验证了所提方法的可行性。     

空间滞后模型的标准化稳健检验及其功效对比分析

在误差项分布未知、模型设定偏误以及不同形式空间布局的复杂条件下，本文提出检验空间滞后模型的标准化稳健LM检验方法，并采用Bootstrap法和Monte Carlo法对统计量的渐进性进行分析. 结果表明：采用Bootstrap法和Monte Carlo法的检验功效均优于现有LM检验方法；对于小样本，结合Bootstrap法与本文提出的统计量进行模型设定的检验更可靠；在空间布局为Group规则时，采用本文提出的统计量进行模型设定的检验效果更好.     

一类参数不确定统一混沌系统的脉冲同步

针对一类参数不确定统一混沌系统的同步问题,提出一种脉冲同步方法.该方法采用响应系统与驱动系统状态变量误差的线性反馈作为脉冲控制信号,驱动两个统一混沌系统达到全局渐近同步.基于脉冲微分方程理论,给出了统一混沌系统一组新的全局渐近同步判据,特别地,当脉冲间距与脉冲控制增益相等时,给出了更为简单和实用的同步判据,同时讨论了脉冲间距对同步性能的影响,仿真结果验证了方法的有效性.     

Robust Estimation for Partial Functional Linear Regression Model Based on Modal Regression

This paper presents a robust estimation procedure by using modal regression for the partial functional linear regression, which combines the common linear model with the functional linear regression model. The outstanding merit of the new method is that it is robust against outliers or heavy-tail error distributions while performs no worse than the least-square-based estimation method for normal error cases. The slope function is fitted by B-spline. Under suitable conditions, the authors obtain the convergence rates and asymptotic normality of the estimators. Finally, simulation studies and a real data example are conducted to examine the finite sample performance of the proposed method. Both the simulation results and the real data analysis confirm that the newly proposed method works very well.     

双应力恒加试验Weibull分布型产品置信可靠性评估模型

为了有效快速评估高可靠性长寿命产品在正常应力条件下的可靠性，提出了一种双应力恒加试验Weibull分布型产品置信可靠性评估模型。首先，采用加速寿命试验(accelerated life test，ALT)技术，建立广义Eyring-Weibull可靠性模型，假定试验各应力水平组合下Weibull分布的形状参数相同，且尺度参数与各应力水平组合间呈对数线性关系。其次，给出了Weibull分布定时截尾双应力恒加试验的极大似然估计(maximum likelihood estimation，MLE)方法、与似然函数相关的Fisher信息矩阵以及模型参数的渐近协方差矩阵，构造了模型参数和一些可靠性指标的渐近置信区间。最后，通过仿真算例证明了所提方法的可行性。     

双应力恒加试验Weibull分布型产品置信可靠性评估模型

为了有效快速评估高可靠性长寿命产品在正常应力条件下的可靠性,提出了一种双应力恒加试验Weibull分布型产品置信可靠性评估模型。首先,采用加速寿命试验(accelerated life test,ALT)技术,建立广义Eyring-Weibull可靠性模型,假定试验各应力水平组合下Weibull分布的形状参数相同,且尺度参数与各应力水平组合间呈对数线性关系。其次,给出了Weibull分布定时截尾双应力恒加试验的极大似然估计(maximum likelihood estimation,MLE)方法、与似然函数相关的Fisher信息矩阵以及模型参数的渐近协方差矩阵,构造了模型参数和一些可靠性指标的渐近置信区间。最后,通过仿真算例证明了所提方法的可行性。     

基于LMI的模糊控制器设计

对于许多实际的非线性系统,状态变量往往不能获取或难于测量。因此设计模糊状态观测器来估计状态变量是非常必要的。针对T-S模糊模型近似描述的非线性系统,提出了一种基于线性矩阵不等式(LMI)的具有区域极点配置功能的模糊控制器和模糊状态观测器的设计方法。首先利用并行分布补偿(PDC)设计思想和基于线性矩阵不等式(LMI)的极点配置理论,将闭环系统的全局渐进稳定性要求,性能指标及控制量约束条件统一到线性矩阵不等式框架内。然后求解线性矩阵不等式族获得控制器和观测器参数。最后将该设计方法应用于倒立摆的平衡控制中,通过仿真曲线可以看出该方法设计的控制器可使倒立摆稳定并满足指定的性能指标,因此该设计方法是有效的。     

16QAM调制下BICM-ID系统的最优多维映射

研究16QAM星座调制下比特交织编码调制迭代译码(BICM-ID)系统的多维映射设计.通过对渐进误比特概率的分析,得到用以映射设计的距离准则.进一步利用修正的分段二进制切换算法(MBSA)搜索,得到准静态瑞利衰落信道下渐进性能近最优的四维16QAM映射.仿真结果表明,采用四维16QAM映射的BICM-ID系统大幅改善了系统的渐进性能.     

ON WEIGHTED RANDOMLY TRIMMED MEANS

A class of robust location estimators called weighted randomly trimmed means are introduced and not only their consistency and asymptotic normality are proved, but their influence functions, asymptotic variances and breakdown points are also derived. They possess the same breakdown points as the median, and some of them own higher asymptotic relative efficiencies at the heavy-tailed distributions than some other well-known location estimators; whereas the trimmed means, Winsorized means and Huber＇s M-estimator possess higher asymptotic relative efficiencies at the light-tailed distributions, in which Huber＇s M-estimator is the most robust.