电路中的最小熵产生率原理

将不可逆过程热力学中的熵产生率概念推广应用到稳恒电路，给出了Ｐｒｉｇｏｇｉｎｅ最小熵产生率原理可适用于稳恒电路的电动力学证明。     

基于最小输出熵的盲反卷积方法

针对多通道卷积混叠模型，基于信息理论的最小熵准则，利用单时间点观测样本给出了一类多通道盲反卷积方法，这种方法不同于其它方法的地方在于考虑了源和观测信号的上下文信息。     

基于粗糙熵的三支加权变形熵

粗糙集理论是关于不确定性信息处理的一种重要理论,其中的多种信息度量都具有有效的不确定性刻画功能.借鉴传统粗糙熵,构建三支加权变形熵.首先,利用粗糙熵的形式结构,采用三支概率提出三支变形熵,得到不完全的粒化单调性.进而变换贝叶斯概率公式,构建三支加权变形熵,得到完全粒化单调性以及三支信息系统性.三支加权变形熵推进了粗糙熵,有益于粗糙集的不确定性表示及应用.     

广义误差分布熵系数与最小相对熵的研究

为直观描述分布尾部特征及两分布之间的差异程度,基于Kulllback-Leibler距离研究广义误差分布熵系数的变动情况,从另一角度说明正态分布满足最大熵原理,尾部特征极不明显,且推导出两个广义误差分布之间的最小相对熵及性质,克服了相对熵的非对称性质,并且确定了不同参数的变动范围对应的最小相对熵形式。     

中国南北地震带中北部最小完整性震级的探讨

用古登堡──里克特公式ｌｇＮ＝ａ－ｂＭ对中国南北地震带中北部（３３°～４０°Ｎ，１０３．５°～１０７°Ｅ）公元１年至１９９０年Ｍ≥５．０地震进行了整体分析。发现１９００年以前资料丢失严重，最小完整性震级为６．０；１９００年以后资料比较完整，最小完整性震级为５．０，从而较为可靠地确定了不同时间段内未遗漏的地震震级下限。     

带有叉熵约束的最小叉熵优化问题的求解

研究了带有叉熵约束的最小叉熵优化问题的求解问题.根据对偶理论,提出了一个简单的几何规划,该方法把一个带有叉熵约束的叉熵优化问题转化成了一个对偶规划,而对偶规划是一个只需要解决一个带有线性约束的凸规划问题,比较容易计算.     

随机系统的最小熵控制

本文放弃传统的MSE准则,从信息论观点出发,发展了随机系统的一种最小熵(ME)控制方法,并从ME控制的等价性、控制限度、存在性、唯一性及必要条件等方面,研究了ME控制的合理性和实用性。ME方法是一种全局分析法,它不仅包含了MSE和MAP准则,且由于全文在整个推导中并未假定高斯性、线性和非时变等,因而原则上适用于诸如非高斯、非线性、时变等传统方法难以处理的复杂系统;不仅适用于工程系统,将其推广到决策、社会、经济等领域会更为自然和切合实际。     

电路中的最小熵产生率原理

将不可逆过程热力学中的熵产生率概念推广应用到稳恒电路，给出了Ｐｒｉｇｏｇｉｎｅ最小熵产生率原理可适用于稳恒电路的电动力学证明。     

效用风险熵

本文提出由客观状态的不确定性和结果价值两方面因素造成的效用风险的概念，定义并构造效用风险函数和效用风险熵的函数表达式，剖析其主要数学特性，阐明效用风险函数和效用风险熵作为客观状态和决策行动方案的效用风险测度函数的合理性．     

基于二维灰度直方图的最小模糊熵分割方法

本文在一维最大模糊熵分割方法的基础上，根据图像目标和背景内部像素灰度值的一致性和集中性，提出了一种新的图像分割隶属度函数，从而得到最小模糊熵分割方法．本文还针对传统的基于一维灰度直方图的模糊熵分割方法不能反应图像的空间信息，抗噪声能力差的缺点，提出了基于二维灰度直方图的模糊熵分割算法．本实验结果证明，最小模糊熵分割方法对于某些图像的分割效果要好于最大模糊熵分割效果，而二维分割方法对于绝大多数图像，都具有很强的鲁棒性和抗噪能力，分割效果明显优于一维的方法，而且方便地推广到其他的一维熵分割方法中。     

异构系统信息集成的数据仓库方法

从某制造型企业信息系统现状出发，说明企业信息集成的重要性，提出了采用数据仓库的方法，在企业原有异构信息系统的基础上进行信息集成，并结合该企业实际情况，说明了这个方法的实现过程。     

基于深度置信网络和信息融合技术的轴承故障诊断

提出一种基于深度置信网络(DBN)和信息融合技术的轴承故障诊断新方法。首先采用集合经验模式分解将轴承振动时域信号分解为若干个固有模态函数,并分别输入至若干个DBN中进行故障状态识别,然后通过简单投票法将每个DBN识别的结果进行决策层信息融合,从而得到轴承故障的最终诊断结果。通过对单负载和多负载下不同类型和不同损伤程度的滚动轴承故障诊断进行实例分析,验证了本文方法的有效性和精确性。     

Measuring visibility using digital photography

An automatic digital photography visibility system (DPVS) is presented, which can directly measure and monitor horizontal visibility during daytime through digital shooting. After shooting a scene of given black object and background via its CCD digital camera, the system can capture and transfer photographic images in the camera to a computer, as well as process the digital images and calculate the value of visibility. The formulas for calculating visibility with this method and analysing the effect of non-black object on measured results have also been derived. And then the comparison of DPVS observations with a Lidar-visibility measurements has been carried out. The results show that the average deviation and relative average deviation of visibility acquired by DPVS from lidar-visibility measurements are respectively within 0.927 km and 6.68%.     

Test of GBAS integrity monitoring system using GPS simulator

In recent years, many countries are developing aircraft navigation systems using GNSS(Global Navigation Satellite System),because GNSS has many technical and economic benefits. International organizations as ICAO(International Civil Aviation Organization) and RTCA(Radio Technical Commission for Aeronautics) set up international standards of GBAS(Ground Based Augmentation System)using GNSS and recommend countries to develop GBAS that is based on the standards. To go with the international stream, Korea Airport Cooperation has also developed GBAS. For evaluating the system,KAC and Seoul National University have performed flight tests of the developed GBAS several times and have concluded that the system has good accuracy enough to be used in aircrafts. At that time, the purpose of tests was focused on accuracy of GBAS. But integrity of the system which is important for safety of aircrafts was not tested sufficiently,because it is impossible to make erroneous situations of real GPS signals. So, at this time, we used GPS simulator which can generate GPS signals with satellite failure scenarios. The GPS simulator used in this test generates GPS signals by the scenarios organized in advance.The scenarios can include pseudorange and carrier phase error, parity error and etc. So we organized several scenarios which can includes potential errors of GPS signals and many possible cases for testing the system effectively and accurately. And we tested integrity function of the GBAS system by using GPS signals generated by the simulator.This paper introduces the implemented integrity monitoring system and algorithms used in the tests. And it describes the scenarios of satellite failure. Finally, this paper shows the results of tests.     

基于信息传播的微博用户影响力度量

信息传播和用户影响力度量是目前微博研究的基础和热点方向。为了定量地研究用户影响力,提出基于用户消息传播范围的用户影响力量化定义,并给出用户影响力的计算方法。在真实数据集上对算法的验证结果显示,与其他用户影响力度量方法相比,本文提出的方法计算复杂性低、指标稳定性高,尤其适合于需要限定数据集、限定时间段的具体应用场景。     

考虑结构一致性和内容完整性的重定向图像质量评价

针对适应不同宽高比显示设备全屏显示的重定向图像的视觉质量问题,提出了一种基于像素级结构一致性和内容完整性的重定向图像质量评价模型。该模型首先使用后向配准建立重定向图像和参考图像之间的像素级对应关系;其次考虑到注意力转移的问题,采用像素级宽高比相似性偏差指数计算重定向图像在显著区域和全局的结构一致性,并利用图像组成变化获取图像内容完整性;最后通过内容完整性和结构一致性的线性组合实现重定向图像质量评价。实验结果表明,提出的模型不仅对重定向图像质量评价的效果好,而且可以在内容完整性和结构一致性的二维评估图中观察不同重定向算法的行为,适用于重定向算法比较、选择和优化。     

基于电热模拟的电迁移可靠性诊断及时钟完整性分析

为诊断大规模集成电路设计过程中电迁移可靠性及分析时钟信号完整性,开发一种用于集成电路片上时钟信号模拟软件Etsim3。该模拟软件考虑了集成电路自热效应,通过电热耦合模拟以及金属连线温度分布解析模型获得更准确的集成电路芯片表面以及各金属连线网络上的温度分布。模拟结果表明,考虑集成电路自热效应前后,电迁移诊断以及时钟信号完整性分析结果都有了较大程度上的改变,Etsim3可以得到更为精确的分析以及诊断结果。     

Selectivity estimation using compressed spatial information

Spatial selectivity estimation is one of the essential studies to get query responses rapidly and accurately with the limitation of memory space. Currently, there exist several spatial selectivity estimation techniques such as random sampling, histogram, and parametric. Especially, Cumulative Density Histogram guarantees accurate estimation for rectangle object which has multiple-count problem. However, it requires large memory space because of retaining four sub-histograms for spatial data. Therefore in this paper, we propose a new technique Cumulative Density Wavelet Histogram, called CDWH, which is the combination of Cumulative Density Histogram and Haar Wavelet Transform, a compressed technique. The proposed method simultaneously takes full advantage of their strong points, high accuracy provided by the former and economization of memory space supported by the latter. Consequently, our technique is able to support estimates with relatively low error and retain similar estimates even if memory space is small.     

基于负信息的改进多假设定位算法

为了克服多假设定位算法在特征非唯一环境中假设数量大、收敛速度慢的问题,提出了利用负信息的改进算法.改进算法首先分析"传感器未检测到环境特征"的事件为定位提供的信息,建立与传感器模型类似的负信息模型.其次,在算法流程中考虑传感器数据中未包含期望特征和未收到传感器数据的情况,在假设权重的评价中加入负信息因子,从数学形式上相当于增加一组独立传感器,为定位提供了额外的信息.仿真实验表明,该算法能够减少假设数量,加快算法收敛,并能够在特定条件下解决多假设定位算法无法唯一定位的问题.     

Selecivity estimation using compressed spatial information

Spatial selectivity estimation is one of the essential studies to get query responses rapidly and accurately with the limitation of memory space. Currently, there exist several spatial selectivity estimation techniques such as random sampling, histogram, and parametric. Especially，Cumulative Density Histogram guarantees accurate estimation for rectangle object which has multiple-count problem. However，it requires large memory space because of retaining four sub-histograms for spatial data. Therefore in this paper， we propose a new technique Cumulative Density Wavelet Histogram，called CDWH，which is the combination of Cumulative Density Histogram and Haar Wavelet Transform，a compressed technique. The proposed method simultaneously takes full advantage of their strong points，high accuracy provided by the former and economization of memory space supported by the latter. Consequently，our technique is able to support estimates with relatively low error and retain similar estimates even if memory space is small.