错误结果反馈对追踪任务学习迁移的影响

采用电脑追踪任务探讨错误结果反馈(KR)对运动技能学习迁移的影响.抽取在校大学生,随机分为正确KR组、错误KR组、混合KR组(组间性别均衡设计).在第1-3 d,3组受试者练习时分别获得正确的KR、错误的KR,或者获得25次正确KR后,再获得25次错误KR.正确的KR是每次追踪误差的毫秒数,错误的KR则是正确KR数值+10 mm.在第4 d,3组受试者分剐在无KR的条件下,用原任务进行保持测试10次,之后再操作两个迁移任务各10次.显示:KR在一致性时机任务和电脑追踪任务中的作用机理类似,当可以获得KR时,学习者将它作为觉察和纠正操作错误的信息源:错误KR会带来迁移测试绩效的偏差.提示:学习者形成自身觉察错误能力是运动技能学习的关键,实践工作者应根据运动情境的特点,合理地提供结果反馈,以促进运动技能的学习.     

基于颜色信息的多机器鱼并行视觉跟踪算法

在多仿生机器鱼协作系统 (MRFS)中,如何快速、准确获取多机器鱼运动信息和环境信息是决策和控制的基础。介绍了MRFS中视觉子系统的实现及其多目标实时跟踪策略。结合机器鱼本体和场地背景的特征,提出了一种基于色度直方图和饱和度直方图的自适应阈值分割算法 ;同时,结合计算机并行处理技术,利用MMX指令和SSE指令,对整个跟踪算法进行了并行性优化。该视觉子系统已成功应用于MRFS中,能实时跟踪自由游动的机器鱼和多个障碍物.     

基于单目视觉的疲劳自动检测

提出了一种基于单目视觉的疲劳检测系统。首先检测人脸,然后对头部进行跟踪,在可靠人脸的基础上,定位并且跟踪眼睛,提取眼角与眼睑特征。通过对眼睛及头部状态的疲劳检测来决定是否触发警告。实验证明系统具有一定的可靠性与准确性。     

Chaos analysis of discharge current based on tracking test of phenolic resin

In tracking test,discharge is a complicated process and comparative tracking index(CTI)has wide variation.To evaluate tracking resistance,the chaos analysis of discharge current is presented based on the tracking test ofphenolic resin in accordance with IEC601 12.According to the characteristics of statistical self-similarity and complexity of discharge current,the largest Lyapunov exponent is calculated,and the 2-dimensional attractor ofdischarge current is reconstructed.Moreover,the attractors of discharge current and recurrence plots of different discharge states are reconstructed.The results indicate that the chaos attractors have different characteristics in evolutionary tracks,the topological structure and grain direction of recurrence plots show significant differences.The chaos attractor can describe the tracking process,the recurrence plot can identify the tracking state clearly,while its arithmetic is simple.     

IP智能探测与追踪系统设计

为确保对网络入侵行为的跟踪与控制,采用IP探测技术,在Microsoft Visual C＋＋8．0与Microsoft Office Access 2007在CZ88．NET IP地址库基础上实现了基于HIDS思想的IP智能追踪系统．系统能够准确定位人侵IP物理位置,获得了良好的实验效果,为系统安全审计与入侵追踪提供了较好保证．     

On maximum power point tracking control strategy for variable speed constant frequency wind power generation

Based on the characteristic of AC-excited variable speed constant frequency （VSCF） wind power generation, the vector control technique was applied in a doubly fed induction generator （DFIG）. Maximum wind energy or maximum output power point can be tracked by decoupling control of active power and reactive power. The research result shows that the net power of generation system delivered to grid in maximum wind energy tracking mode is not the most. We presented a novel maximum power point tracking （MPPT） control strategy by analyzing the DFIG mathematic model and power relations which delivered the maximum power to the grid. The maximum power point could be tracked automatically without measuring wind speed in the control strategy and the control was independent of optimal turbine power curve, which had excellent dynamic and static performances and robustness. Simulation and experimental results testify the accuracy and validity of the control strategy.     

卫星天线稳定跟踪平台的总体模块化设计

针对多种武器系统对稳定跟踪平台的要求,对两轴卫星天线稳定跟踪平台进行了研究与设计。分析了天线稳定跟踪的基本原理,给出了控制方案,完成了平台的模块化设计和工作流程设计,经实验,该平台具有较好的跟踪能力。     

基于主题的舆情跟踪方法研究及性能评价

舆情跟踪是对媒体信息流中的热点话题进行实时追踪,是近年来自然语言处理领域的研究热点。实现该任务的核心技术是进行文本分类,运用信息增益以及互信息计算特征项权重,提取向量空间模型中文档表示的有效特征;分别采用Rocchio、K-Nearest Neighbor(KNN)、Bayes方法对于给定主题的事件实现舆情跟踪。在测试集上的最优性能F-Measure值达到86.2%。舆情跟踪在信息安全等领域具有广阔的应用前景,为用户及时判断网络热点事件的发展趋势提供有效指导依据。     

视觉运动追踪及其在体育运动中的应用与启示

运动员的视觉运动追踪能力是众多运动项目获得优异比赛成绩的关键因素,也是近些年运动心理学研究的重要问题。运用文献综述法对国内外关于视觉运动追踪的基本理论、研究范式及其在体育运动中的应用进行剖析,总结以往研究所取得的成果和存在的不足,探讨视觉运动追踪研究对体育运动成绩的影响与启示,为后续相关研究提供一定的思路与方法借鉴,为运动员心理选材及心理技能训练方法与策略提供理论参考和实证依据。     

A maximum power point tracker for photovoltaic energy systems based on fuzzy neural networks

To extract the maximum power from a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array must be tracked closely. The non-linear and time-variant characteristics of the PV array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP for traditional control strategies. We propose a fuzzy neural network controller （FNNC）, which combines the reasoning capability of fuzzy logical systems and the learning capability of neural networks, to track the MPP. With a derived learning algorithm, the parameters of the FNNC are updated adaptively. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the FNNC. Simulation results show that the proposed control algorithm provides much better tracking performance compared with the filzzy logic control algorithm.