共查询到19条相似文献，搜索用时 187 毫秒
1.
在指数分布定数截尾情形下,当先验分布中的超参数部分未知时,在加权平方损失下构造了刻度参数的参数型经验Bayes(PEB)估计,研究了其在均方误差(MSE)准则下相对于一致最小方差无偏估计(UMVUE)的优良性,并获得了PEB估计的大样本性质.当先验分布中的超参数完全未知时,通过数值模拟比较了PEB估计和UMVUE的均方误差,获得了其优良性.最后,通过数值模拟的结果,获得了PEB区间估计的优良性. 相似文献
2.
3.
本文研究了一类范数有界不确定离散状态时滞系统的鲁棒控制问题.通过采用新的方法,得到了使得系统鲁棒渐近稳定的改进的时滞相关准则,设计了使得系统鲁棒镇定的线性无记忆状态反馈控制器.所得时滞相关准则以严格线性矩阵不等式形式表示,且包含了更少的变量. 相似文献
4.
提出非齐次等式约束线性回归模型回归系数的一个新的有偏估计,即综合条件岭估计,讨论了综合条件岭估计的性质,在一定的条件下,综合条件岭估计的样本总方差、均方误差、均方误差矩阵均分别小于约束最小二乘估计的相应误差.在综合条件岭估计下,条件岭估计和条件根方估计为其特例,从而统一了条件岭估计和条件根方估计的理论. 相似文献
5.
多元线性模型中最小二乘估计新的相对效率 总被引：2，自引：0，他引：2
定义了广义行列式的概念，并在多元线性模型中，引入了回归系数的最小二乘估计与最佳线性无估计的一种新的相对效率．利用广义行列式的性质和矩阵分析的方法，通过对相对效率下界的研究，推广了Bloomfield-Watson定理。 相似文献
6.
文章简要介绍了线性模型Ｍ估计（包括ＬＳ和Ｌ１估计）大样本理论研究状况,提出了一些有待解决的重要问题。 相似文献
7.
利用文[7]提出的相对效率定义,研究文[8]、[9]非齐次等式约束线性回归模型回归系数的狭义条件岭估计和广义条件岭估计的效率,证明在一定条件下,狭义条件岭估计和广义条件岭估计的效率比约束最小二乘估计的效率高,并且广义条件岭估计的效率比狭义条件岭估计的效率高,从而进一步证明了在病态的模型中,有偏估计优于无偏估计。 相似文献
8.
在已知的线性模型中,考虑加权最小二乘估计与线性无偏最小方差估计的结果的差异。发现在两种条件下,加权最小二乘估计与线性无偏最小方差估计的结果趋于一致。 相似文献
9.
本文采用基于新息准则的快速子空间跟踪算法解决了直接序列扩频(DS/SS)信号的扩频码盲估计问题.该方法具有较高的运算效率,克服了传统方法在PN码盲恢复时实时处理上的困难,理论分析和数值仿真结果表明,该方法在较低的输入信噪比下能够完成对PN码的正确估计,与特征值分解、神经网络等算法相比具有更好的性能. 相似文献
10.
线性规划技术已被应用于许多学科。有一类统计问题,根据其实质可视为线性规划问题,或者说可转化为线性规划问题进行求解。本文讨论在回归分析中利用线性规划技术对线性模型中的回归系数进行估计。最小二乘法通常用作最优拟合的准则。其优点在于消除了正负误差相互抵消的问题,突出了大的拟合误差的作用以及计算上方便。我们能求解普通的线性方程组 相似文献
11.
泊松回归模型常常用于计数数据的研究中,然而在实际数据中零值的比例可能远远大于泊松分布中取零值的概率,而且这些零值通常都有其特殊含义.此外计数数据可能是分组数据,即观测到的数据不是确切值而只是已知其落在某一个区间范围之内;或者某些特定的数据,例如工资,要先对它进行人为的分组然后再进行分析.考虑一种零膨胀泊松半参数回归模型来处理上述分组计数数据.该模型中泊松分布的期望与协变量之间采用部分线性连接函数,而零值的概率与协变量之间采用线性连接函数.利用Sieve极大似然估计方法来估计该回归模型中参数和非参数函数,并提出了一种得分检验方法来检验是否存在零膨胀.在一定正则条件下,获得了Sieve极大似然估计的渐近性质,证明了参数部分的估计是强相合,渐近正态及渐近有效的;同时非参数函数的估计达到了最优收敛速度.模拟研究表明,估计和检验方法效果都比较好,最后将此模型和推断方法应用于一组公共卫生领域实际数据研究. 相似文献
12.
This paper is concerned with the robust state estimation problem for semi-Markovian switching complex-valued neural networks with quantization effects (QEs). The uncertain parameters are described by the linear fractional uncertainties (LFUs). To enhance the channel utilization and save the communication resources, the measured output is quantized before transmission by a logarithmic quantizer. The purpose of the problem under consideration is to design a full-order state estimator to estimate the complex-valued neuron states. Based on the Lyapunov stability theory, stochastic analysis method, and some improved integral inequalities, sufficient conditions are first derived to guarantee the estimation error system to be globally asymptotically stable in the mean square. Then, the desired state estimator can be directly designed after solving a set of matrix inequalities, which is robust against the LFUs and the QEs. In the end of the paper, one numerical example is provided to illustrate the feasibility and effectiveness of the proposed estimation design scheme. 相似文献
13.
《Journal of The Franklin Institute》2022,359(16):9168-9192
In this paper we propose an interval-based state estimator for continuous-time linear systems with discrete-time measurements using an event-triggered mechanism and an explicit reachability method. An output injection method combined with a state variables permutation procedure are applied to design the robust estimator. In addition, the convergence of the proposed set-membership state estimator and the existence of a lower bound on the inter-event times are shown. Throughout a numerical example, the performance of this estimator are illustrated and compared to related works. 相似文献
14.
In this paper a new integrated observer-based fault estimation and accommodation strategy for discrete-time piecewise linear (PWL) systems subject to actuator faults is proposed. A robust estimator is designed to simultaneously estimate the state of the system and the actuator fault. Then, the estimate of fault is used to compensate for the effect of the fault. By using the estimate of fault and the states, a fault tolerant controller using a PWL state feedback is designed. The observer-based fault-tolerant controller is obtained by the interconnection of the estimator and the state feedback controller. We show that separate design of the state feedback and the estimator results in the stability of the overall closed-loop system. In addition, the input-to-state stability (ISS) gain for the closed-loop system is obtained and a procedure for minimizing it is given. All of the design conditions are formulated in terms of linear matrix inequalities (LMI) which can be solved efficiently. Also, performance of the estimator and the state feedback controller are minimized by solving convex optimization problems. The efficiency of the method is demonstrated by means of a numerical example. 相似文献
15.
本文用矩阵的秩这个工具考察了有限维线性系统具有二次性能指标的最优输出反馈问题，得到了一个必要条件。特殊情形下，这一条件可以演化为最优输出反馈增益与观测矩阵的乘积即为状态反馈增益这个相当清晰的关系。 相似文献
16.
This paper is concerned with the problem of state estimation for a class of discrete-time switched positive linear systems (SPLS) with average dwell time (ADT) switching. By utilizing the multiple linear copositive Lyapunov function (MLCLF) approach, the ADT switching is introduced to tackle the state estimation of the underlying system. Some sufficient conditions of the existence of the estimator are derived in terms of a set of linear matrix inequalities for the underlying systems with ADT switching. The results for the SPLS under arbitrary switching can be easily obtained by reducing MLCLF to the common linear copositive Lyapunov function used for the system in the literature. Finally, a numerical example is given to show the validity of the obtained theoretical results. 相似文献
17.
《Journal of The Franklin Institute》2019,356(16):9881-9906
This paper is concerned with robust stability analysis of second-order linear time-varying (SLTV) systems with time-varying uncertainties (perturbations). With the specific Lyapunov functions, a simple and neat algebraic criterion for testing uniformly asymptotic stability of SLTV systems are derived. Without transformation to a system of first-order equations, the new conditions are imposed directly on the time-varying coefficient matrices of the system. The main feature of the proposed algebraic criterion is that the uncertain coefficient matrices are time-varying and not necessarily symmetric. Finally, the proposed stability conditions are used to design the extending space structures system of the spacecraft. Simulation results are provided to illustrate the convenience and effectiveness of the proposed method. 相似文献
18.
J.M. Lowerre 《Journal of The Franklin Institute》1977,303(6):517-526
For the linear statistical model y = Xb + e, X of full column rank estimates of b of the form (C + X′X)+X′y are studied, where C commutes with X′X and Q+ is the Moore-Penrose inverse of Q. Such estimators may have smaller mean square error, component by component than does the least squares estimator. It is shown that this class of estimators is equivalent to two apparently different classes considered by other authors. It is also shown that there is no C such that (C + X′X)+X′Y = My, in which My has the smallest mean square error, component by component. Two criteria, other than tmse, are suggested for selecting C. Each leads to an estimator independent of the unknown b and σ2. Subsequently, comparisons are made between estimators in which the C matrices are functions of a parameter k. Finally, it is shown for the no intercept model that standardizing, using a biased estimate for the transformed parameter vector, and retransforming to the original units yields an estimator with larger tmse than the least squares estimator. 相似文献
19.
This paper studies the distributed Kalman consensus filtering problem based on the event-triggered (ET) protocol for linear discrete time-varying systems with multiple sensors. The ET strategy of the send-on-delta rule is employed to adjust the communication rate during data transmission. Two series of Bernoulli random variables are introduced to represent the ET schedules between a sensor and an estimator, and between an estimator and its neighbor estimators. An optimal distributed filter with a given recursive structure in the linear unbiased minimum variance criterion is derived, where solution of cross-covariance matrix (CCM) between any two estimators increases the complexity of the algorithm. In order to avert CCM, a suboptimal ET Kalman consensus filter is also presented, where the filter gain and the consensus gain are solved by minimizing an upper bound of filtering error covariance. Boundedness of the proposed suboptimal filter is analyzed based on a Lyapunov function. A numerical simulation verifies the effectiveness of the proposed algorithms. 相似文献