高斯型耦合Tavis-Cummings模型的纠缠特性

研究了高斯型耦合Tavis-Cummings模型的量子纠缠特性,利用量子约化熵研究了相干光场-双原子之间的纠缠,利用Negativity熵研究了两原子之间的纠缠,运用数值计算方法讨论了原子垂直于腔轴的运动速度和系统的初态对场-原子以及原子-原子纠缠的影响.结果表明,两种纠缠具有相似的时间演化规律,但对应于同一时刻,场-原子间的纠缠越强,两原子间的纠缠越弱.原子的运动速度对纠缠具有明显的调制作用;光场的初始光子数越大,熵的Rabi振荡频率越大,振幅越小;而改变原子的初态时,熵的时间演化规律是相似的.     

几种TCP协议下F、G函数的研究

随着网络技术的不断提高,一些新型的高速网络投入使用,产生了一系列如TCP拥塞控制算法,其中Reno协议、Vegas协议、RED协议以不同的方式解决了网络拥塞的问题。通过在以上3种协议模型下对F、G函数进行推导,用对偶方程求解的方法,比较3种协议的优劣,为网络模型的建立打下基础。     

农村通信网络需求及建设模式分析

在分析农村通信需求的基础上,通过实际案例,介绍了农村通信网络建设的主要思路和建设模型。     

安防系统在信息大厦中的应用

结合信息大厦安防系统的设计实践,从出入门控制系统、防盗报警系统、电视监控系统等方面对安防系统在工程中的应用进行了介绍。     

基于格网模型的三维地形可视化

地形是自然界中具有复杂特征的景物之一,格网模型具有结构简单,数据直观的优点,是地形建模的有效模型.在地形建模的基础上,经过消隐处理、光照处理等处理过程后,可以实现三维真实感地形的显示.提出了基于格网模型的地形建模技术,并给出了消隐处理、光照处理的方法和实验结果,从而实现三维真实感地形的可视化.     

地空路径水凝物交叉极化特性研究

水凝物的交叉极化预报模式对10GHz以上频段使用正交极化频率复用的卫星通信系统设计具有重要意义.基于ITU-R与OPEX数据库的地空雨致交叉极化数据和二阶小变量近似的预报模式,给出了一种改进的雨致交叉极化预报模式.与其它模式比较表明,这一模式的预测精度有明显提高.     

MOS器件的ESD失效

静电放电(ESD)对半导体器件,尤其是金属氧化物半导体(MOS)器件的影响日趋凸显,而相关的研究也是备受关注.综述了静电放电机理和3种常用的放电模型,遭受ESD应力后的MOS器件失效机理,MOS器件的两种失效模式;总结了ESD潜在性失效灵敏表征参量及检测方法;并提出了相应的静电防护措施.     

Infrared Radiance Simulation and Application under Cloudy Sky Conditions Based on HIRTM

An algorithm based on hyperspectral infrared cloudy radiative transfer model (HIRTM) is introduced and a simulation method for infrared image of the generation geostationary meteorological satellite is proposed. Based on the parameters from weather research and forecast (WRF), such as the water content, atmospheric temperature, and humidity profile, the simulation data for the advanced Himawari imager (AHI) infrared radiative (IR) channels of Himawari-8 are obtained. Simulated results based on HIRTM agree well with the observed data. Further, the movement, development, and change of the cloud are well predicated. And the simulation of IR cloud image for the weather forecast has been obtained. This paper provides an improved method for evaluation and improvement of regional numerical model for weather forecast.     

基于树结构分层随机森林在非约束环境下的头部姿态估计

头部姿态估计是人类行为和注意力的关键,受到光照、噪声、身份、遮挡等许多因素的影响。为了提高非约束环境下的估计准确率和鲁棒性,该论文提出了树结构分层随机森林在非约束环境下的多类头部姿态估计。首先,为了消除不同环境的噪声影响,提取人脸区域的组合纹理特征,对人脸区域进行积极人脸子区域的分类,分类结果作为树结构分层随机森林的先验知识输入;其次,提出了一种树结构分层随机森林算法,分层估计多自由度下的头部姿态;再次,为了增强算法的分类能力,使用自适应高斯混合模型作为多层次子森林叶子节点的投票模型。在多个公共数据集上的多种非约束实验环境下进行头部姿态估计,最终实验结果表明所提算法在不同质量的图像上都有很好的估计准确率和鲁棒性。     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.