带曲率补偿的带隙基准电流源的设计

简单介绍了带隙基准源的基本原理,给出了一款基于Widlar结构的带曲率补偿的带隙基准电压电流源的设计方法,通过采用TSMC₀.5μm工艺库对电路进行仿真,在-40～150℃的温度范围内,其带隙基准的输出具有12ppm/℃的温度系数,电流基准的输出具有42ppm/℃。此外,文中还对曲率补偿电路的工作原理进行了分析,并且通过仿真波形对曲率补偿的工作机制进行了讨论。     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.     

DM-CTSA: a discriminative multi-focused and complementary temporal/spatial attention framework for action recognition

Neural Computing and Applications - Video-based human action recognition remains a challenging task. There are three main limitations: (1) Most works are only restricted to single temporal scale...     

五自由度上肢康复机器人动力学建模及仿真

分析了五自由度上肢康复机器人的系统结构,构建出新的系统简化模型,并利用拉格朗日动力学法建立康复机器人简化动力学方程,提出了一类机器人简化建模的新方法.在Matlab中用V-realm Builder工具建立5-DOF上肢康复机器人三维虚拟仿真模型并进行虚拟仿真.仿真结果表明,简化的动力学模型在康复机器人控制中应用效果良好,理论响应曲线与实际响应曲线误差较小.该方法建模过程简单、快捷、有效,适合现代计算技术的发展,为康复机器人系统的优化设计及运动控制提供了理论依据.     

A Polynomial Algorithm for Computing Elementary Siphons in a Class of Petri Nets

A set of elementary siphons plays a key role in the development of deadlock prevention policies for automated manufacturing systems. This paper addresses the computation problem for elementary siphons in a subclass of Petri nets which are basic systems of simple sequential processes with resources (BS³PR) and can model many automated manufacturing systems. An algorithm for enumerating elementary siphons is established by the one‐to‐one relationship between maximal perfect resource‐transition circuits (MPCs) and strict minimal siphons. A set of MPCs is first computed, followed by a set of elementary siphons in a BS³PR. The presented algorithm is proved to have polynomial‐time complexity. An example is used to illustrate the algorithm.     

Optimal Path Problems with Second-Order Stochastic Dominance Constraints

This paper studies optimal path problems integrated with the concept of second order stochastic dominance. These problems arise from applications where travelers are concerned with the trade off between the risks associated with random travel time and other travel costs. Risk-averse behavior is embedded by requiring the random travel times on the optimal paths to stochastically dominate that on a benchmark path in the second order. A general linear operating cost is introduced to combine link- and path-based costs. The latter, which is the focus of the paper, is employed to address schedule costs pertinent to late and early arrival. An equivalent integer program to the problem is constructed by transforming the stochastic dominance constraint into a finite number of linear constraints. The problem is solved using both off-the-shelf solvers and specialized algorithms based on dynamic programming (DP). Although neither approach ensures satisfactory performance for general large-scale problems, the numerical experiments indicate that the DP-based approach provides a computationally feasible option to solve medium-size instances (networks with several thousand links) when correlations among random link travel times can be ignored.     

动载作用下机场刚性道面模态参数识别研究

关于机场道面刚性结构参数识别问题,研究移动荷载作用下机场刚性道面识别系统中,传统弹性、粘弹性解析识别精度的不足,建立了移动荷载作用下弹性支承边界、弹性嵌固边界和实际边界条件下的道面板的运动方程,提出了一种基于变分法、功互等定理的Kelvin粘弹性地基上道面板系统的识别方法。同时根据最小二乘法准则进行反演,拟合实测动挠度和理论动挠度,从而识别出地基反应模量K。经仿真与实测结果可知,改进方法在保证识别速度的前提下可以显著提高识别精度,具有很好的应用价值,为机场刚性道面的设计、参数识别和质量评价等提供理论依据。