In this paper a local maximum principle for the singular discrete-time linear systemMx(k)=φx(k-1)+Bu(k-1)is investigated.By using this local maximum principle we can discussthe linear-quadratic optimal regulator prob...In this paper a local maximum principle for the singular discrete-time linear systemMx(k)=φx(k-1)+Bu(k-1)is investigated.By using this local maximum principle we can discussthe linear-quadratic optimal regulator problem and the minimum energy problem for singulardiscrete-time linear systems.展开更多
In this paper, we exploit the concept of data fusion in hybrid localization systems by combining different TOA (Time of Arrival) observables coming from different RATs (Radio Access Technology) and characterized by di...In this paper, we exploit the concept of data fusion in hybrid localization systems by combining different TOA (Time of Arrival) observables coming from different RATs (Radio Access Technology) and characterized by different precisions in order to enhance the positioning accuracy. A new Maximum Likelihood estimator is developed to fuse different measured ranges with different variances. In order to evaluate this estimator, Monte Carlo simulations are carried out in a generic environment and Cramer Rao Lower Bounds (CRLB) are investigated. This algorithm shows enhanced positioning accuracy at reasonable noise levels comparing to the typical Weighted Least Square estimator. The CRLB reveals that the choice of the number, and the configuration of Anchor nodes, and the type of RAT may enhance positioning accuracy.展开更多
为提升局部最大同步挤压变换估算瞬时频率的精度,本文结合2阶局部最大同步挤压变换(Second-order Local Maximum Synchrosqueezing Transform,SLMSST)和动态规划(Dynamic Optimization,DO)方法提出一种识别时变结构瞬时频率的新方法。...为提升局部最大同步挤压变换估算瞬时频率的精度,本文结合2阶局部最大同步挤压变换(Second-order Local Maximum Synchrosqueezing Transform,SLMSST)和动态规划(Dynamic Optimization,DO)方法提出一种识别时变结构瞬时频率的新方法。该方法首先通过引入2阶瞬时振幅与相位得到精度更高的2阶瞬时频率估算位置。其次,搜索频率方向上时频系数的局部最大值所对应的2阶瞬时频率位置并根据这些位置对时频系数进行重排,从而得到2阶局部最大同步挤压变换后的瞬时频带。再次,运用动态规划法在限定频带范围内提取瞬时频率曲线。通过一组数值算例和一个时变拉索试验验证了所提新方法的有效性,研究结果表明:相比既有的局部最大同步挤压变换算法,2阶局部最大同步挤压变换和动态规划的联合算法不仅具有较好的精度,而且具有更好的时频聚集性。展开更多
为解决局部最大同步挤压变换算法识别的频率精度不足及频带能量发散的问题,提出一种改进算法并将之命名为改进局部最大同步挤压变换方法(improved local maximum synchrosqueezing transform,ILMSST)。该方法首先对瞬时频率(instantaneo...为解决局部最大同步挤压变换算法识别的频率精度不足及频带能量发散的问题,提出一种改进算法并将之命名为改进局部最大同步挤压变换方法(improved local maximum synchrosqueezing transform,ILMSST)。该方法首先对瞬时频率(instantaneous freguency,IF)位置进行多次迭代,从而获得更高精度的瞬时频率位置。其次,搜索短时傅里叶系数模极大值的位置并上下平移该位置,得到初步估算的频带并将频带外的短时傅里叶系数归零。最后,搜索频率方向上短时傅里叶系数的局部最大值所对应的瞬时频率位置,根据这些位置对时频系数进行重排,进而得到细化的瞬时频带。通过2组数值算例、1个7层钢筋混凝土剪力墙振动台试验和1个时变拉索试验验证了所提新方法的有效性,研究结果表明:相比现有的局部最大同步挤压变换方法,改进算法不仅提高了瞬时频率的估算精度,而且改善了响应信号瞬时频带的时频聚集性。展开更多
文摘In this paper a local maximum principle for the singular discrete-time linear systemMx(k)=φx(k-1)+Bu(k-1)is investigated.By using this local maximum principle we can discussthe linear-quadratic optimal regulator problem and the minimum energy problem for singulardiscrete-time linear systems.
文摘具有混合记忆的自步对比学习(Self-paced Contrastive Learning,SpCL)通过集群聚类生成不同级别的伪标签来训练网络,取得了较好的识别效果,然而该方法从源域和目标域中捕获的行人数据之间存在典型的分布差异,使得训练出的网络不能准确区别目标域和源域数据域特征。针对此问题,提出了双分支动态辅助对比学习(Dynamic Auxiliary Contrastive Learning,DACL)框架。该方法首先通过动态减小源域和目标域之间的局部最大平均差异(Local Maximum Mean Discrepancy,LMMD),以有效地学习目标域的域不变特征;其次,引入广义均值(Generalized Mean,GeM)池化策略,在特征提取后再进行特征聚合,使提出的网络能够自适应地聚合图像的重要特征;最后,在3个经典行人重识别数据集上进行了仿真实验,提出的DACL与性能次之的无监督域自适应行人重识别方法相比,mAP和rank-1在Market1501数据集上分别增加了6.0个百分点和2.2个百分点,在MSMT17数据集上分别增加了2.8个百分点和3.6个百分点,在Duke数据集上分别增加了1.7个百分点和2.1个百分点。
文摘In this paper, we exploit the concept of data fusion in hybrid localization systems by combining different TOA (Time of Arrival) observables coming from different RATs (Radio Access Technology) and characterized by different precisions in order to enhance the positioning accuracy. A new Maximum Likelihood estimator is developed to fuse different measured ranges with different variances. In order to evaluate this estimator, Monte Carlo simulations are carried out in a generic environment and Cramer Rao Lower Bounds (CRLB) are investigated. This algorithm shows enhanced positioning accuracy at reasonable noise levels comparing to the typical Weighted Least Square estimator. The CRLB reveals that the choice of the number, and the configuration of Anchor nodes, and the type of RAT may enhance positioning accuracy.
文摘针对传统无监督领域自适应方法扩展到多工况滚动轴承故障诊断场景适用性较弱的问题,提出了一种多源域自适应残差网络(multi-source domain adaptive residual network,MDARN),通过对齐来自多个源域的相关子域,从而提高模型在多工况下的故障诊断性能。首先,利用ResNeXt残差网络从源域和目标域充分提取可迁移特征;然后,引入局部最大平均差异(local maximum mean difference,LMMD)准则,以两个源域的子域为基础对齐目标域中相关子域,减少相关子域间和全局域间的分布差异;最后,利用美国凯斯西储大学轴承数据集和MFS机械综合故障试验台产生的真实的轴承振动数据集,对所提方法进行了试验验证。结果表明,该方法在多工况下的平均故障诊断精度高达99.76%。与现有代表性方法相比,所提方法具有更好的故障诊断效果。
文摘为提升局部最大同步挤压变换估算瞬时频率的精度,本文结合2阶局部最大同步挤压变换(Second-order Local Maximum Synchrosqueezing Transform,SLMSST)和动态规划(Dynamic Optimization,DO)方法提出一种识别时变结构瞬时频率的新方法。该方法首先通过引入2阶瞬时振幅与相位得到精度更高的2阶瞬时频率估算位置。其次,搜索频率方向上时频系数的局部最大值所对应的2阶瞬时频率位置并根据这些位置对时频系数进行重排,从而得到2阶局部最大同步挤压变换后的瞬时频带。再次,运用动态规划法在限定频带范围内提取瞬时频率曲线。通过一组数值算例和一个时变拉索试验验证了所提新方法的有效性,研究结果表明:相比既有的局部最大同步挤压变换算法,2阶局部最大同步挤压变换和动态规划的联合算法不仅具有较好的精度,而且具有更好的时频聚集性。
文摘为解决局部最大同步挤压变换算法识别的频率精度不足及频带能量发散的问题,提出一种改进算法并将之命名为改进局部最大同步挤压变换方法(improved local maximum synchrosqueezing transform,ILMSST)。该方法首先对瞬时频率(instantaneous freguency,IF)位置进行多次迭代,从而获得更高精度的瞬时频率位置。其次,搜索短时傅里叶系数模极大值的位置并上下平移该位置,得到初步估算的频带并将频带外的短时傅里叶系数归零。最后,搜索频率方向上短时傅里叶系数的局部最大值所对应的瞬时频率位置,根据这些位置对时频系数进行重排,进而得到细化的瞬时频带。通过2组数值算例、1个7层钢筋混凝土剪力墙振动台试验和1个时变拉索试验验证了所提新方法的有效性,研究结果表明:相比现有的局部最大同步挤压变换方法,改进算法不仅提高了瞬时频率的估算精度,而且改善了响应信号瞬时频带的时频聚集性。