Creation and control of high-dimensional multi-partite classically entangled light

Vector beams, non-separable in spatial mode and polarisation, have emerged as enabling tools in many diverse applications, from communication to imaging. This a...     

Sensing mechanism of Ag/α-MoO3 nanobelts for H2S gas sensor

Sensing mechanism is still a big problem in the field of gas sensor.In-depth study of the sensing mecha-nism can provide better ideas for the design of sensing ...     

EDGE网络的规划及资源配置研究

本文在现有网络分析的基础上,进行了EDGE数据网的规划,并通过仿真对规划结果进行了验证,最后对语音和数据网络的资源配置方法进行了研究,提出了相应的资源配置方法。     

奥运火炬大同传递电视转播纪实

为了迎接百年奥运圣火于6月27日的到来,大同电视台要进行全程电视直播．同时,还要协助中央电视台和山西电视台完成起点和终点现场节目录制的联络和信号光纤传输任务,为此,之前的一个月就进行着大量的技术准备工作。由于火炬传递路线几经调整,电视转播的技术方案也随之进行了多次的修改和完善。     

A 20.8-Gbps Dual-Carrier Wireless Communication Link in 220-GHz Band

With the successful demonstration of terahertz (THz) high-speed wireless data transmission,the THz frequencies are now becoming a worth candidate for post-5G wi...     

ptp通讯在锌电解供电优化系统中的研究与应用

以提高锌电解供电系统的自动化程度、实现网络控制为目的,在分析了系统总体结构和控制原理的基础上,重点讨论了ptp通讯在系统中的研究与应用;ptp通讯网络以S7-300PLC为主站,以两台晶闸管数字触发器为从站,实现电流给定和触发角反馈等信号的传输,其通讯协议简单,开发成本低,与Profibus网一道组成的控制网抗干扰能力强,可靠性高,有力地保证了锌电解供电优化系统安全运行,为锌电解提高整流效率、节约电能提供了保障.     

Multiple costs based decision making with back-propagation neural networks

The current research investigates a single cost for cost-sensitive neural networks (CNN) for decision making. This may not be feasible for real cost-sensitive decisions which involve multiple costs. We propose to modify the existing model, the traditional back-propagation neural networks (TNN), by extending the back-propagation error equation for multiple cost decisions. In this multiple-cost extension, all costs are normalized to be in the same interval (i.e. between 0 and 1) as the error estimation generated in the TNN. A comparative analysis of accuracy dependent on three outcomes for constant costs was performed: (1) TNN and CNN with one constant cost (CNN-1C), (2) TNN and CNN with two constant costs (CNN-2C), and (3) CNN-1C and CNN-2C. A similar analysis for accuracy was also made for non-constant costs; (1) TNN and CNN with one non-constant cost (CNN-1NC), (2) TNN and CNN with two non-constant costs (CNN-2NC), and (3) CNN-1NC and CNN-2NC. Furthermore, we compared the misclassification cost for CNNs for both constant and non-constant costs (CNN-1C vs. CNN-2C and CNN-1NC vs. CNN-2NC). Our findings demonstrate that there is a competitive behavior between the accuracy and misclassification cost in the proposed CNN model. To obtain a higher accuracy and lower misclassification cost, our results suggest merging all constant cost matrices into one constant cost matrix for decision making. For multiple non-constant cost matrices, our results suggest maintaining separate matrices to enhance the accuracy and reduce the misclassification cost.     

Extracting the optimal dimensionality for local tensor discriminant analysis

Supervised dimensionality reduction with tensor representation has attracted great interest in recent years. It has been successfully applied to problems with tensor data, such as image and video recognition tasks. However, in the tensor-based methods, how to select the suitable dimensions is a very important problem. Since the number of possible dimension combinations exponentially increases with respect to the order of tensor, manually selecting the suitable dimensions becomes an impossible task in the case of high-order tensor. In this paper, we aim at solving this important problem and propose an algorithm to extract the optimal dimensionality for local tensor discriminant analysis. Experimental results on a toy example and real-world data validate the effectiveness of the proposed method.     

高压开关运动系统等效质量的计算

提出用“基本形块”分割法来计算形状复杂构件的转动惯量,这种方法易于写出通用算式,并便于用作图法简化计算.在速度比方面,介绍了作图解法和适于计算机使用的算式.     

迭代学习控制用于StatCom阻尼区域间振荡的研究

ＳｔａｔＣｏｍ一般安装在长距离输电线路上,用于提高电力系统的稳定性,阻尼振荡,提高电压控制的精度及系统的传输能力。