统计模式识别的研究

模式识别的基本目标就是在有监督和无监督的情况下进行分类,在模式识别的各种模型中,基于统计的方法已经被广泛的研究并应用于实际.一些新的技术和方法的引入（神经网络和支持向量机方法）也促进了该领域发展,文章研究了基于统计的模式识别的进展情况,给出了模式识别的概念、原理、方法并对各种方法进行了相关的评述.     

关于双语课程《数字电子技术》学习状况的调查与思考

以问卷调查的形式,通过描述性统计和定量分析,对我校双语课程《数字电子技术》学习状况进行了调查和分析,在此基础上,对双语教学提出了一些建议.     

基于CTV100平台的DPTV系统的研究与实现

从硬件和软件两方面详细阐述了基于CTV100平台的DPTV系统,并给出了总体设计框图和设计流程图。本项目采用意法半导体公司(ST)的CTV100解决方案,实现了对传统模拟电视信号的高效数字域处理,显著提高了电视画面的图像质量;并通过采用基于32bitCPU的OS20嵌入式操作系统,实现了多种传统模拟电视无法实现的功能。     

研究性学习中的心理学思想探析

研究性学习视学生为一个完整的人，注重学生个性的培养，重视学生潜能的开发以及整体素质的协调，这其中渗透着激发学生学习动机、使学生达到自我实现等心理学思想．该文对研究性学习的几个特点的心理学思想进行了分析。     

Distributed and Parallel Component Library

Software component library is the essential part of reuse-based software development. It is shown that making use of a single component library to store all kinds of components and from which components are searched is very inefficient. We construct multi-libraries to support software reuse and use PVM as development environments to imitate Iargescale computer, which is expected to fulfill distributed storage and parallel search of components efficiently and improve software reuse.     

大学生学习焦虑心理研究

通过分析大学生学习焦虑心理的成因以及学习焦虑控制问题。论述了大学生学习焦虑心理与学习成绩的关系。     

Using genetically-defined rodent strains for the identification of hippocampal traits relevant for two-way avoidance behavior: a non-invasive approach

Summary Genetically-defined rodent strains permit the identification of hippocampal traits which are of functional relevance for the performance of two-way avoidance behavior. This is exemplified here by analyzing the relationship between infrapyramidal mossy fibers (a tiny projection terminating upon the basal dendrites of hippocampal pyramidal neurons) and two-way avoidance learning in about 800 animals. The necessary steps include 1) identification of structural traits sensitive to selective breeding for extremes in two-way avoidance, 2) testing the robustness of the associations found by studying individual and genetical correlations between hippocampal traits and behavior, 3) establishing causal relationships by Mendelian crossing of strains with extreme structural traits and studying the behavioral consequences of such structural randomization, 4) confirming causal relationships by manipulating the structural variable in inbred (isogenic) strains, thereby eliminating the possibility of genetic linkage, and 5) ruling out the possibility of spurious associations by studying the correlations between the hippocampal trait and other behaviors known to depend on hippocampal functioning.In comparison with the classical lesion approach for identifying relationships between brain and behavior, the present procedure appears to be superior in two aspects: it is non-invasive, and it focuses automatically on those brain traits which are used by natural selection to shape behaviorally-defined animal populations, i.e., it reveals the natural regulators of behavior.     

提高西德MNPJ型毛圈圆纬机压针三角与舌针使用寿命的研究

本文通过西德MNPJ型毛圈圆纬机编织过程的受力分析和机械润滑试验,提出了提高三角和舌针使用寿命的途径;同时又对该机三角系统的材料进行了研究,提出了自制三角系统的看法。     

Learning attention-based strategies to cooperate for multi-agent path finding

Multi-agent path finding (MAPF) is a challenging multi-agent systems problem where all agents are required to effectively reach their goals concurrently with not colliding with each other and avoiding obstacles. In MAPF, it is a challenge to effectively express the observation of agents, utilize historical information, and effectively communicate with neighbor agents. To tackle these issues, in this work, we proposed a well-designed model that utilizes the local states of nearby agents and outputs an optimal action for each agent to execute. We build the local observation encoder by using residual attention CNN to extract local observations and use the Transformer architecture to build an interaction layer to combine local observations of agents. With the purpose of overcoming the deficiency of success rate, we also designed a new evaluation index, namely extra time rate (ETR). The experimental results show that our model is superior to most previous models in terms of success rate and ETR. In addition, we also completed the ablation study on the model, and the effectiveness of each component of the model was proved.     

基于强化学习的电磁悬浮型磁浮列车悬浮控制

为了保证磁浮列车的安全、可靠运行,研究了悬浮系统在参数摄动条件下的悬浮控制问题。首先,对电磁悬浮（EMS）型磁浮列车的基本悬浮单元建模,给出了电流控制模型;然后,建立了悬浮系统的强化学习环境以及软演员-评论家（SAC）智能体,并设计了加速训练的奖励函数与“吸死”处理方案;最后,提出了基于强化学习的悬浮控制方法。与传统比例-积分-微分（PID）控制方法的对比结果表明,本方法具有更快的动态响应,在损失50%线圈匝数或磁极面积变化时具有更好的跟踪精度。