Augmented Lagrangians with Adaptive Precision Control for Quadratic Programming with Equality Constraints: Corrigendum and Addendum

In this paper we give corrections to our paper on an augmented Lagrangian type algorithm for strictly convex quadratic programming problems with equality constraints.     

New Approach to Model Validation and Fault Diagnosis

The paper presents a new approach to model validation and fault diagnosis problems for a class of uncertain systems in which the uncertainty is described by an integral quadratic constraint. The new approach is developed by applying methods from linear quadratic optimal control theory. This leads to a method for model validation and fault diagnosis which is based around a robust Kalman filter type structure.     

Gauss噪声扰动下的FitzHugh-Nagumo系统的随机稳定性

在Gauss噪声扰动下FitzHugh-Nagumo系统的随机稳定性是该文的研究目的．通过研究随机FitzHugh-Nagumo系统的动力学行为, 证明其存在唯一的、具有指数混合速度的不变测度．最后, 考察当噪声趋于0时不变测度的渐近行为．     

Mixture estimation with state-space components and Markov model of switching

The paper proposes a recursive algorithm for estimation of mixtures with state-space components and a dynamic model of switching. Bayesian methodology is adopted. The main features of the presented approach are: (i) recursiveness that enables a real-time performance of the algorithm; (ii) one-pass elaboration of the data sample; (iii) dynamic nature of the model of switching active components; (iv) orientation at explicit solutions with exploitation of numerical procedures only in those parts which cannot be computed analytically; (v) systematic approach to the Bayesian mixture estimation theory.     

Evaluation of the multiobjective ant colony algorithm performances on biobjective quadratic assignment problems

The difficulty of resolving the multiobjective combinatorial optimization problems with traditional methods has directed researchers to investigate new approaches which perform better. In recent years some algorithms based on ant colony optimization (ACO) metaheuristic have been suggested to solve these multiobjective problems. In this study these algorithms have been reported and programmed both to solve the biobjective quadratic assignment problem (BiQAP) instances and to evaluate the performances of these algorithms. The robust parameter sets for each 12 multiobjective ant colony optimization (MOACO) algorithms have been calculated and BiQAP instances in the literature have been solved within these parameter sets. The performances of the algorithms have been evaluated by comparing the Pareto fronts obtained from these algorithms. In the evaluation step, a multi significance test is used in a non hierarchical structure, and a performance metric (P metric) essential for this test is introduced. Through this study, decision makers will be able to put in the biobjective algorithms in an order according to the priority values calculated from the algorithms’ Pareto fronts. Moreover, this is the first time that MOACO algorithms have been compared by solving BiQAPs.     

正态线性模型中误差方差的二次型估计的容许性

设Ｙ遵从Ｎ（Ｘβ，σ２Ｉｎ），秩（Ｘ）＜ｎ，在平方损失下，本交给出σ２的二次型估计在整个估计类中可容许的充要条件．     

基于最小交易量和交易费用的多阶段模糊投资组合

考虑了在摩擦市场下的多阶段模糊投资组合模型,基于半绝对方差风险函数,建立了带有最小交易量和交易费用限制的收益最大化多阶段模糊投资组合模型.利用绝对值函数的性质,将模型转化为混合整数线性规划形式,并通过实例验证了模型的可行性,最后对模型与基于可能性均值和可能性方差的多阶段模糊投资组合模型进行了对比,分析了模型的优越性,并验证了模型的可行性.     

Event-based state estimation for a class of complex networks with time-varying delays: A comparison principle approach

The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator.     

The Accuracy and the Computational Complexity of a Multivariate Binned Kernel Density Estimator

The computational cost of multivariate kernel density estimation can be reduced by prebinning the data. The data are discretized to a grid and a weighted kernel estimator is computed. We report results on the accuracy of such a binned kernel estimator and discuss the computational complexity of the estimator as measured by its average number of nonzero terms.     

A New Generator of Probability Models: The Exponentiated Sine-G Family for Lifetime Studies

In this article, we propose the exponentiated sine-generated family of distributions. Some important properties are demonstrated, such as the series representation of the probability density function, quantile function, moments, stress-strength reliability, and Rényi entropy. A particular member, called the exponentiated sine Weibull distribution, is highlighted; we analyze its skewness and kurtosis, moments, quantile function, residual mean and reversed mean residual life functions, order statistics, and extreme value distributions. Maximum likelihood estimation and Bayes estimation under the square error loss function are considered. Simulation studies are used to assess the techniques, and their performance gives satisfactory results as discussed by the mean square error, confidence intervals, and coverage probabilities of the estimates. The stress-strength reliability parameter of the exponentiated sine Weibull model is derived and estimated by the maximum likelihood estimation method. Also, nonparametric bootstrap techniques are used to approximate the confidence interval of the reliability parameter. A simulation is conducted to examine the mean square error, standard deviations, confidence intervals, and coverage probabilities of the reliability parameter. Finally, three real applications of the exponentiated sine Weibull model are provided. One of them considers stress-strength data.