Robust and asymptotically unbiased estimation of extreme quantiles for heavy tailed distributions

A robust and asymptotically unbiased extreme quantile estimator is derived from a second order Pareto-type model and its asymptotic properties are studied under suitable regularity conditions. The finite sample properties of the proposed estimator are investigated with a small simulation experiment.     

Risk Sensitive Filtering with Poisson Process Observations

In this paper we consider risk sensitive filtering for Poisson process observations. Risk sensitive filtering is a type of robust filtering which offers performance benefits in the presence of uncertainties. We derive a risk sensitive filter for a stochastic system where the signal variable has dynamics described by a diffusion equation and determines the rate function for an observation process. The filtering equations are stochastic integral equations. Computer simulations are presented to demonstrate the performance gain for the risk sensitive filter compared with the risk neutral filter. Accepted 23 July 1999     

Study of the UBM to copper interface robustness of solder bumps in flip chip packages

Shear tests on SnAg solder bumps were performed with a reduced height to the surface for a high shear force on the under bump metallurgy (UBM) to redistribution layer (RDL) copper interface. By this the failure mechanism of UBM–RDL delamination after stress tests simulating several assembly reflows could be reproduced. A design of experiment was done with corner wafers at worst case conditions for topography and interface clean. TEM cross sections confirmed nano scale carbon residues in the interface when reducing the clean efficiency. This results in a mechanically weakened interface with a present electrical contact. The shear test with reduced height is a more severe test beyond the JEDEC test to verify the bump robustness. This is important when existing bump technologies are used for flip chip package solutions with increased solder reflow requirements.     

The Robust Design with the Pole Assignment

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On sensitivity of detector structures to contaminants in non-white mixture noise model

In this paper, we study the structure of the locally optimal detector in non-white transformation noise with -contaminated marginal density. We show that each of the memoryless nonlinearities in the detector can be at least approximately represented as a term for the nominal density plus a correction term in closed form that is directly proportional to . The approximations are found, by simulation, to be good in most cases except when is large and the tail weight of the contaminant is large. We also show that the eigenfunctions of the bivariate noise density can be put in a similar form.     

Global stabilization of a dynamic von Kármán plate with nonlinear boundary feedback

We consider a fully nonlinear von Kármán system with, in addition to the nonlinearity which appears in the equation, nonlinear feedback controls acting through the boundary as moments and torques. Under the assumptions that the nonlinear controls are continuous, monotone, and satisfy appropriate growth conditions (however, no growth conditions are imposed at the origin), uniform decay rates for the solution are established. In this fully nonlinear case, we do not have, in general, smooth solutions even if the initial data are assumed to be very regular. However, rigorous derivation of the estimates needed to solve the stabilization problem requires a certain amount of regularity of the solutions which is not guaranteed. To deal with this problem, we introduce a regularization/approximation procedure which leads to an approximating problem for which partial differential equation calculus can be rigorously justified. Passage to the limit on the approximation reconstructs the estimates needed for the original nonlinear problem.The material of M. A. Horn is based upon work partially supported under a National Science Foundation Mathematical Sciences Postdoctoral Research Fellowship. I. Lasiecka was partially supported by National Science Foundation Grant NSF DMS-9204338.     

基于节点冗余容量动态控制的复杂网络鲁棒性研究

针对传统级联失效模型中冗余参数固定不变的问题,该文综合考虑节点受攻击程度不同和失效过程中网络拓扑的动态变化,建立了基于节点冗余容量动态控制(DRC)的级联失效模型.通过定义网络相变临界因子θ衡量节点失效引发级联失效的概率,分析了网络鲁棒性与θ之间的相关性,并结合度分布函数详细推导了θ的解析表达式,基于解析表达式提出了两种网络鲁棒性提升策略.仿真结果表明,在模型网络和真实网络中,根据被攻击节点度的不同,通过调整节点初始负载参数可以有效提高目标网络的鲁棒性;DRC模型下级联失效传播范围较τ Motter-Lai(ML)模型显著减小.     

The application of experimental design to the robustness testing of a method for the determination of drug-related impurities by capillary electrophoresis

Summary Robustness testing of capillary electrophoresis methods is an important part of method validation. Appropriate use of experimental designs can be employed in this robustness testing. In this study experimental designs were used in the assessment of a capillary electrophoresis method used to determine drug related impurities. Initially a fractional factorial screening design was used to identify the critical parameters which were found to be pH and voltage. A central composite design was then performed to evaluate the response surfaces for pH and voltage which showed operation at the optimum pH and voltage values.     

A closer look at analytical signals

Analytical chemistry will be considered here as the measurement science of chemistry that generates, treats, and evaluates signals which contain information about the composition and structure of samples. Analytical information is always obtained from signals. Characteristics and peculiarities of analytical signals will be considered from a very general point of view. A mathematical model of the influencing of signals will be given from which essential performance characteristics of analytical methods can be derived, e.g. sensitivity, cross-sensitivity, specificity, selectivity, and ruggedness (robustness).     

Practical digest for evaluating the uncertainty of analytical assays from validation data according to the LGC/VAM protocol

The estimation of the measurement uncertainty of analytical assays based on the LGC/VAM protocol from validation data is fully revisited and discussed in the light of the study of precision, trueness and robustness.