机动目标跟踪的非线性算法

卡尔曼滤波器对线性高斯滤波问题能提供最优解, 而对目标运动模型、观测方程等要求的非线性就不再适合,提出了一种机动目标自适应非线性粒子滤波算法-" 粒子滤波器"(Particle Filters PF)法, 这种方法不受线性化误差和高斯噪声假定的限制,适用于任何状态转换或测量模型, 分析比较了粒子滤波(PF)与扩展卡尔曼滤波算法(EKF) 的滤波精度、运算量等方面指标.给出了基于典型非线性模型的算法仿真, 仿真结果表明粒子滤波新方法优于EKF对机动目标跟踪.     

Asymmetric information and third-party intervention in civil wars

I study a two-period model of conflict with two combatants and a third party who is an ally of one of the combatants. The third party is fully informed about the type of her ally but not about the type of her ally’s enemy. In a signaling game, I find that if the third party is unable to give a sufficiently high assistance to her ally, then there exists a unique separating equilibrium in which the third party’s expected intervention causes her ally’s enemy to exert more effort than in the absence of third-party intervention; this worsens the conflict.     

基于重构相空间AD-SVM的短期电力负荷预测

利用重庆市九龙坡区电网2009年7月1日000-10月8日4：00 99 d共2 380个历史电力负荷数据,分析其特点和规律.将构建混沌理论的平均位移（AD）法和支持向量机（SVM）相结合,提出了一种新的短期电力负荷预测模型.通过仿真计算,将结果与神经网络法预测结果进行对比,可得新方法能较好反应数据变化趋势,并且具备较好的拟合能力,能够提高负荷预测精度.在实际短期电力负荷预测中,可优先选用平均位移法与支持向量机相结合的新方法.     

Sequential learning versus no learning in Bayesian regression models

We consider two regression models: linear and logistic. The dependent variable is observed periodically and in each period a Bayesian formulation is used to generate updated forecasts of the dependent variable as new data is observed. One would expect that including new data in the Bayesian updates results in improved forecasts over not including the new data. Our findings indicate that this is not always true. We show there exists a subset of the independent variable space that we call the “region of no learning.” If the independent variable values for a given period in the future are in this region, then the forecast does not change with any new data. Moreover, if the independent variable values are in a neighborhood of the region of no learning, then there may be little benefit to wait for the new data and update the forecast. We propose a statistical approach to characterize this neighborhood which we call the “region of little learning.” Our results provide insights into the trade‐offs that exist in situations when the decision maker has an incentive to make an early decision based on an early forecast versus waiting to make a later decision based on an updated forecast. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 532–548, 2014     

神经网络在雷达装备故障趋势预测中的应用

为了提高预测精度,在雷达装备状态监测与故障趋势预测系统中引入基于指数衰减的神经网络预测模型。通过普通BP网络预测模型引出基于指数衰减的神经网络预测模型,经验证预测精度较高。并介绍了雷达装备状态监测与故障趋势预测系统构成,此系统对于雷达装备的早期故障预测和预防性维修具有重要意义。     

战略预警系统数据集成模型研究

设计了一种数据集成在战略预警系统中的应用模型,模型采用XML语言在.NET环境下用C#语言实现战略预警系统的中间件,该中间件将各个子系统粘合在一起,从而形成战略预警系统,该模型为目前急需建设的战略预警系统提供了一种解决方案。     

再入飞行器落点准确度的统计分析

本文研究再入飞行器的落点准确度(系统性偏差)的检验和估计方法。首先,文中引入了准确度的容许限的概念,在此基础上给出了Bayes验后加权概率比检验方法。关于落点系统偏差的估计,讨论了Bayes估计方法及带有约束的Bayes估计方法。文中注意了充分运用试验前的信息,以便使落点系统偏差的评估能在小子样场合下进行。     

考虑验前信息可信度时的Bayes估计

研究了考虑验前信息可信度时的验前分布和Bayes估计算法,给出了正态总体参数的Bayes估计方法。以导弹落点散布的估计为例,说明了考虑验前信息可信度时Bayes估计有明显的改善,即具有更好的可信度。     

一种新的非线性/非高斯滤波方法

自主滤波方法是一种递归式贝叶斯估计方法 ,该方法采用一组抽样值来近似目标状态的概率密度函数 ,可用于非线性系统模型和观测模型、非高斯观测噪声条件下的滤波。将该算法与扩展卡尔曼滤波方法进行了比较 ,仿真结果表明 ,该算法性能优于扩展卡尔曼滤波方法     

Bayesian sampling plans for exponential distributions with interval censored samples

This article studies the problem of designing Bayesian sampling plans (BSP) with interval censored samples. First, an algorithm for deriving the conventional BSP is proposed. The BSP is shown to possess some monotonicity. Based on the BSP and using the property of monotonicity, a new sampling plan modified by the curtailment procedure is proposed. The resulting curtailed Bayesian sampling plan (CBSP) can reduce the duration time of life test experiment, and it is optimal in the sense that its associated Bayes risk is smaller than the Bayes risk of the BSP if the cost of the duration time of life test experiment is considered. A numerical example to compute the Bayes risks of BSP and CBSP and related quantities is given. Also, a Monte Carlo simulation study is performed to illustrate the performance of the CBSP compared with the BSP. The simulation results demonstrate that our proposed CBSP has better performance because it has smaller risk. The CBSP is recommended. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 604–616, 2015