Generation of hyperentangled four-photon cluster state via cross-Kerr nonlinearity

We propose a scheme for generating a hyperentangled four-photon cluster state that is simultaneously entangled in polarization modes and spatial modes. This scheme is based on linear optical elements, weak cross-Kerr nonlinearity, and homodyne detection. Therefore, it is feasible with current experimental technology.     

基于红外光谱分析的新型物质分析算法及实验研究

提出了一种基于红外光谱分析技术的物质识别算法以解决定性、定量的进行红外光谱分析时所遇到的难题。通过将欧氏距离相似性判定和光谱分析传统方法的结合,完成了该算法的理论分析并开发了相应的物质分析软件。通过物质分析实验验证了该算法的可行性,实验结果表明该算法应用于测试混合物光谱分析时分析准确度优于96%。通过分析实验结果表明可知:该算法能够程序化地实现物质的现场快速检测,并保持很高的精确度,能够满足食品安全领域的光谱分析需求。     

基于核方法的模拟电路故障诊断

核方法通过非线性映射将原始数据嵌入到高维特征空间,然后进行线性分析和处理,为基于知识的数据分析带来新的方法和模式;传统方法无法解决故障特征数据维数高、在故障样本交叠严重时多分类性能较差的问题,因此在电路故障特征数据预处理阶段,提出了分步骤分别在时域对电路输出电压波形进行小波包分析和在频域测量电路幅频特性的方法来提取电路故障特征;预处理后的故障特征向量只是8维向量,减少了SVM的训练时间;将该方法应用于国际标准电路中的CTSV滤波器电路的故障诊断,结果表明:该方法能突出不同故障的特性,故障诊断正确率达到98.57%(414/420)。     

基于直推式学习的网络故障诊断算法

网络故障的及时诊断能够保证日常工作、学习和生活能够正常进行。传统的基于监督式学习的诊断方法依赖于大量具有鉴别意义的样本,这在实际情况中通常难以得到满足。针对上述问题,本文提出了一种基于直推式学习的诊断算法。针对大规模的网络管理的特征数据,本算法利用主成分分析对特征进行降维,并利用新的度量下的特征数据来构建拉普拉斯矩阵;该矩阵能够很好的描述带检测样本和训练样本之间的关系。在此基础上,本文设计了基于直推式学习的目标函数,并利用拉格朗日乘子法完成了优化。实验部分证明了本算法能够在有限数目的带标签的样本的前提下获得精确的分类结果,能够显著提高网络故障诊断的检测率。     

Detecting community structure using label propagation with consensus weight in complex network

Community detection is a fundamental work to analyse the structural and functional properties of complex networks.The label propagation algorithm(LPA) is a near linear time algorithm to find a good community structure. Despite various ubsequent advances, an important issue of this algorithm has not yet been properly addressed. Random update orders within the algorithm severely hamper the stability of the identified community structure. In this paper, we executed the asic label propagation algorithm on networks multiple times, to obtain a set of consensus partitions. Based on these onsensus partitions, we created a consensus weighted graph. In this consensus weighted graph, the weight value of the dge was the proportion value that the number of node pairs allocated in the same cluster was divided by the total number f partitions. Then, we introduced consensus weight to indicate the direction of label propagation. In label update steps,y computing the mixing value of consensus weight and label frequency, a node adopted the label which has the maximum mixing value instead of the most frequent one. For extending to different networks, we introduced a proportion parameter o adjust the proportion of consensus weight and label frequency in computing mixing value. Finally, we proposed an pproach named the label propagation algorithm with consensus weight(LPAcw), and the experimental results showed that he LPAcw could enhance considerably both the stability and the accuracy of community partitions.     

多维谱的简化探测

提出一种利用谱编辑的方法来简化二维谱的探测,使得一张二维谱可以被简化为N条一维谱(N等于二维谱中F1维上的谱线总数),从而达到缩短数据采集时间和减少数据贮存空间的目的。文中给出了运用此方法探测二维碳氢异核相关实验的实例,并分析了由于F1维的谱线不为δ函数而产生的编辑误差的大小,最后将此方法推广到三维的简化探测,即通过对N张二维谱的编辑获得三维谱的信息。     

Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator

Effects of threshold value on detection performance of the modified amplitude-modulated joint transform correlator are quantitatively studied using computer simulation. Fingerprint and human face images are used as test scenes in the presence of noise and a contrast difference. Simulation results demonstrate that this correlator improves detection performance for both types of image used, but moreso for human face images. Optimal detection of low-contrast human face images obscured by strong noise can be obtained by selecting an appropriate threshold value.     

Adaptive detection technique for optical wireless communication over strong turbulence channels

Optical wireless communication (OWC) systems use the atmosphere as a propagation medium, so the atmospheric turbulence effects lead to fading related with signal intensity. The received signal of OWC over strong turbulence channels is assumed to be a mixture of K-distributed fading and Gaussian distributed thermal noise. Second-order spectral analysis is unable to separately estimate the mixed signal. In order to mitigate the fading induced by turbulence, the decision threshold-updating algorithm based on second and higher order cumulants is proposed and is able to operate in an unknown turbulence environment. The performance of the adaptive processing scheme has been evaluated by means of Monte Carlo simulations. Simulation results show the improvement of the bit error rate (BER) performance.     

基于气象因素的集中供热系统热负荷预测研究

为了解决直升机旋翼伺服作动器维修保障过程中训练资源有限,拆装难度高,故障率较高且难以确定故障点等难题,在直升机虚拟维修训练系统(VMTS, Virtual Maintenance Training System)的基础上,提出了应用虚拟仪器检测,确定故障点的直升机故障诊断可视化设计方法。分析了故障诊断过程中仪器、工具、环境等对故障诊断的影响,实现了动态的建立仿真模型和数据处理。通过虚拟仪器和推理机的功能配合,解决了直升机维护中复杂多变的故障诊断难题,形成一个逻辑推理能力强的故障诊断系统。最后以直升机旋翼伺服作动器故障诊断为例,验证该方法的可行性。