无源超高频射频识别系统路径损耗研究

基于射频识别技术原理及Friis传输方程, 导出了自由空间下无源超高频射频识别(RFID) 系统路径损耗表达式. 结合菲涅耳区理论, 分析了菲涅耳余隙及阅读器天线至标签间距两因变量条件下 第一菲涅耳区受阻隔对RFID系统路径损耗的影响, 并提出了双斜率对数距离路径损耗模型. 在开阔室内环境下, 测试了菲涅耳余隙及阅读器天线至标签间距变化时的系统路径损耗. 测试结果表明: 菲涅耳余隙大于第一菲涅耳区半径1.5倍时, 刃形障碍物对系统路径损耗影响较小; 相比传统对数距离路径损耗模型, 双斜率模型标准差减小10%. 关键词： 射频识别 路径损耗 菲涅耳区 线性回归     

大气信道简化单次散射模型

采用椭球坐标系研究非直视日盲紫外光通信的单次散射模型,求解过程中要对有效散射体的体积进行复杂的数值积分并确定三组积分限。为便于分析,使用近似表达式极大简化了复杂单次散射信道模型,得出路径损耗是收发机几何结构与大气散射吸收系数的函数。对传输距离和路径损耗的仿真证明,该近似表达式与原始模型的所得结果吻合很好。利用该近似表达式,分别仿真分析了大气能见度对紫外光通信系统路径损耗和误码率的影响,仿真结果表明,大气能见度并不是越高越好,而是在能见度为10 km时紫外光通信系统有最佳性能。     

Estimation of the Failure Rate in a Partially Accelerated Life Test: A Sequential Approach

Abstract

Consider the situation in which a group of units are put on a partially accelerated life test. It is assumed that the lifelengths of the units are independent and exponentially distributed random variables with common failure rate θ, and that θ is the value of a random variable having a gamma distribution. A two‐stage sequential procedure for estimating θ under the squared error loss is proposed. In the first stage, the units are put on the test under normal stress up to time t, where t is determined as a stopping time that minimizes the expected loss plus cost of running the test. In the second stage, the stress is raised to a higher level for those units that did not fail by time t and held constant until they all fail. The accumulated data are then used to estimate θ with the Bayes estimator.     

不忽略一次项损失时望大特性质量损失函数设计

田口先生提出的质量特性损失函数是用二次项来表示的,对于望大特性而言,质量特性实际上不可能达到无穷大。讨论了不能忽略一次项损失时,望大特性质量损失函数应采用二次式表示。研究了二次式损失函数中一次项损失系数和二次项损失系数确定的方法。比较分析了二次式损失函数中一次项损失和二次项损失的大小。本文的研究结果显示,田口先生经典的二次项损失函数是二次式损失函数的一种形式。实际问题也验证了本文的研究成果。     

Expected Shortfall风险度量下的最优再保险（英文）

为了避免由高理赔额造成的违约,保险公司通常通过签订再保合约将一部分风险转移给再保险公司.近年来对最优再保策略的研究着眼于最小化自留损失的方差,保险公司总风险的value-at-risk或conditional tail expectation.本文研究了在expected shortfall准则下的再保策略.我们给出了最优的增凸转移损失函数,并分别讨论了有无保费限制的情形.     

对称熵损失下成功概率P的E—Bayes估计

研究对称熵损失下成功概率P的Bayes估计和E—Bayes估计,证明了前者的存在性及唯一性．模拟结果表明E-Bayes估计优于极大似然估计和Bayes估计．并将E—Bayes方法应用在证券投资预测之中,预测效果较好．     

Multiple states repetitive group sampling plans with process loss consideration

We propose a multiple state repetitive group sampling plan by considering the process loss. The optimal plan parameters of the proposed plan are selected such that producer’s risk and consumer’s risk are satisfied simultaneously by minimizing the average sample number. The advantages of the proposed plan over the existing sampling plans are given. Extensive tables are provided for practical applications of the proposed plan. Two real world examples are given for the illustration purpose.     

Distribution of maximum loss of fractional Brownian motion with drift

In this paper, we find bounds on the distribution of the maximum loss of fractional Brownian motion with $H\ge 1/2$ and derive estimates on its tail probability. Asymptotically, the tail of the distribution of maximum loss over $[0,t]$ behaves like the tail of the marginal distribution at time $t$.     

A multi-objective mathematical optimization model for process targeting using 100% inspection policy

The selection of the optimal process target is an important problem in production planning and quality control. Such process targeting problems are usually modeled in the literature using a single objective optimization model. In this paper multi-objective optimization is introduced in the process targeting area. The quality characteristic under consideration is normally distributed with unknown mean and known standard deviation, and has two market specification limits. 100% inspection is used as the mean of product quality control. Product satisfies the first specification limit is sold in a primary market at a regular price and products fails the first specification limit and satisfies the second one is sold in a secondary market at a reduced price. The product is reworked if it does not satisfy both specification limits. The developed multi-objective optimization model consists of three objective functions, which are to maximize profit, income and product uniformity using Taguchi quadratic function as a surrogate for product uniformity. An algorithm is proposed to obtain and rank the set of Pareto optimal points. The utility of the model has been demonstrated using a numerical example from the literature with some additional data the new model requires. Sensitivity analysis was conducted and showed that the results of the model are sensitive to changes in process variance. In addition the optimal objectives of the profit function and product uniformity are more sensitive to changes in model parameters than the income function.