融合图嵌入的Smooth-PCANet图像识别算法

主成分分析网络（Principal Component Analysis Network,PCANet）是一种简单的深度学习算法,在图像识别领域具有优秀的性能。然而PCANet在构建网络卷积核时只关注了图像的主分量信息,忽视了近邻像素点之间的位置关系。而通常情况下,图像的相邻像素点具有空间强相关性,因此利用图结构保持像素点的位置近邻关系更有利于网络提取有效特征。因此,我们将图嵌入思想融入PCANet,提出一种新的图像识别算法Smooth-PCANet。为了验证Smooth-PCANet算法的有效性,我们在人脸、手写体字符以及图片等不同数据集上构建实验,并将Smooth-PCANet与多种基于深度学习的图像识别算法作了对比。实验结果证明,Smooth-PCANet算法比PCANet获得了更高的识别性能,并且更有效地避免了过拟合,在小样本训练时具有显著优势。     

A pixel-level local contrast measure for infrared small target detection

Infrared (IR) small target detection is one of the key technologies of infrared search and track (IRST) systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure (PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously. With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker (RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.     

一种有效的红外弱小目标DBT算法研究

作为红外自寻的制导、搜索跟踪和预警等领域的一项关键技术,红外弱小目标检测与跟踪成了红外图像处理领域中的一项重要研究课题。本文采用了"先检测后跟踪(DBT)"的思想对红外小目标进行检测与跟踪,首先采用基于各向异性偏微分方程的背景抑制技术对单帧图像进行抑制,再用最大绝对对比度阈值对红外图像进行分割,最后采用形心跟踪法对小目标点坐标定位。试验证明本文算法应用于目标检测的可行性和有效性。     

基于NSGA-II和多属性决策的防空火力分配

为了解决防空火力分配问题,首先运用NSGA-II算法求出Pareto最优解集,然后运用多属性决策方法对Pareto最优解集中的解进行综合评估,并从中找出一个最优解。用区间数定性描述各属性,建立了防空火力分配的三目标优化模型。描述了NSGA-II算法和多属性决策方法的运算步骤。在仿真算例中,得到了一个最佳防空火力分配方案,说明该方法对于防空火力分配问题有良好的应用价值。     

铜冶炼炉溜槽上方钢梁温度分布研究

为了对有色冶炼厂房框架钢梁耐火稳定性评估提供条件,根据冶炼铜实际工况建立计算模型,数值研究钢梁温度分布,结果表明:在加热初期,钢梁的平均温度和最高温度不断上升,经历10个升温-降温周期后,钢梁的最高温度稳定在220℃左右。钢梁温度与梁的截面尺寸和形状、梁计算截面位置、溜槽与梁相对位置等众多因素有关。梁与溜槽距离越大,梁截面高度越大,翼缘宽度越小,最高温度与平均温度越低;梁长度大小不影响梁最高温度,但梁长度越大平均温度越低。     

一种基于改进SIFT的图像盲取证算法

针对常见的复制粘贴篡改,提出了一种基于改进SIFT（Scale Invariant Feature Transform）的图像篡改检测算法。首先,把待检测图像划分成多个矩形的ROS（Regions of Suspicion）区域,利用改进的SIFT算法提取各个ROS区域的关键点;然后,利用马氏距离原理对特征点对进行筛选与匹配,通过直线将这些匹配点连接起来,对复制粘贴区域进行准确定位。实验表明,该算法不仅降低了运算复杂度,而且对篡改区域的平移、缩放,旋转、亮度调整等,都有很好的检测和定位效果。     

反海盗任务中大中口径舰炮火力应用

在反海盗任务中,大中口径舰炮武器系统可担负对海盗船进行警示或警告性射击,或者直接打击的任务。在对海盗船编队目标特性分析的基础上,以单管大口径舰炮对集群海盗船射击作为研究对象,将射击类型分为警示、警告和阻拦射击,重点分析了对集群海盗船只警告性射击方式,提出了警告性射击修正量的计算方式,最后通过实例仿真证明了该方法的适用性。     

Signature based analysis of m‐Consecutive‐k‐out‐of‐n: F systems with exchangeable components

In this article, we study reliability properties of m‐consecutive‐k‐out‐of‐n: F systems with exchangeable components. We deduce exact formulae and recurrence relations for the signature of the system. Closed form expressions for the survival function and the lifetime distribution as a mixture of the distribution of order statistics are established as well. These representations facilitate the computation of several reliability characteristics of the system for a given exchangeable joint distribution or survival function. Finally, we provide signature‐based stochastic ordering results for the system's lifetime and investigate the IFR preservation property under the formulation of m‐consecutive‐k‐out‐of‐n: F systems. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

基于种群分类的变尺度免疫克隆选择算法

提出了一种基于种群分类的变尺度免疫克隆选择算法.该算法通过对目标函数进行非线性尺度变换,突出了全局最优解的优势地位;建立记忆子群实现了种群代际进化信息的交换;依据亲和度将抗体分为精英子群、普通子群、劣等子群,并对其分别执行自适应高斯变异、均匀变异和消亡更新等策略,增强了算法的局部和全局搜索能力.引入小生境技术提高了抗体...     

Monitoring poisson count data with probability control limits when sample sizes are time varying

This article considers the problem of monitoring Poisson count data when sample sizes are time varying without assuming a priori knowledge of sample sizes. Traditional control charts, whose control limits are often determined before the control charts are activated, are constructed based on perfect knowledge of sample sizes. In practice, however, future sample sizes are often unknown. Making an inappropriate assumption of the distribution function could lead to unexpected performance of the control charts, for example, excessive false alarms in the early runs of the control charts, which would in turn hurt an operator's confidence in valid alarms. To overcome this problem, we propose the use of probability control limits, which are determined based on the realization of sample sizes online. The conditional probability that the charting statistic exceeds the control limit at present given that there has not been a single alarm before can be guaranteed to meet a specified false alarm rate. Simulation studies show that our proposed control chart is able to deliver satisfactory run length performance for any time‐varying sample sizes. The idea presented in this article can be applied to any effective control charts such as the exponentially weighted moving average or cumulative sum chart. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 625–636, 2013