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Robust Disturbance Rejection Based Control with Extended-state Resonant Observer for Sway Reduction in Uncertain Tower-cranes 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 812-827
作者:  Horacio Coral-Enriquez;  Santiago Pulido-Guerrero;  John Cortés-Romero
浏览  |  Adobe PDF(2214Kb)  |  收藏  |  浏览/下载:206/59  |  提交时间:2021/02/22
Active disturbance rejection control (ADRC)  extended state observer (ESO)  tower-crane control  resonant observer  disturbance observer  linear matrix inequality.  
A Linear Quadratic Controller Design Incorporating a Parametric Sensitivity Constraint 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 553-562
作者:  Mohamed Yagoubi
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Linear quadratic control  parametric uncertainties  trajectory sensitivity  non-standard Riccati equation  Lur'e matrix equations  linear time invariant (LMI)  particle swarm optimization.  
Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 286-296
作者:  Bing-Tao Zhang;  Xiao-Peng Wang;  Yu Shen
浏览  |  Adobe PDF(847Kb)  |  收藏  |  浏览/下载:191/50  |  提交时间:2021/02/22
Feature fusion  mild difficulty in falling asleep (MDFA)  decision support tool  sleep issues  optimal feature set.  
Development and Modeling of Remotely Operated Scaled Multi-wheeled Combat Vehicle Using System Identification 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 261-273
作者:  A. N. Ouda;  Amr Mohamed;  Moustafa EI-Gindy;  Haoxiang Lang;  Jing Ren
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Autonomous multi-wheeled vehicle  system identification  all wheel steering  fuzzy logic (FL)  parametric identification.  
Function Projective Lag Synchronization of Chaotic Systems with Certain Parameters via Adaptive-impulsive Control 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 238-247
作者:  Xiu-Li Chai;  Zhi-Hua Gan
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Function projective lag synchronization (FPLS)  adaptive-impulsive  chaotic systems  numerical simulation  Lyapunov stability theory.  
Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 184581-184598
作者:  Liu, Yating;  Wang, Kunfeng;  Li, Xuesong;  Bai, Tianxiang;  Wang, Fei-Yue
Adobe PDF(4276Kb)  |  收藏  |  浏览/下载:235/36  |  提交时间:2020/03/30
Visual tracking  bibliographic analysis  collaboration patterns  research hotspots  parallel vision  
A Novel and Efficient CVAE-GAN-Based Approach With Informative Manifold for Semi-Supervised Anomaly Detection 期刊论文
IEEE ACCESS, 2019, 卷号: 2019, 期号: 7, 页码: 88903-88916
作者:  Bian, Jiang;  Hui, Xiaolong;  Sun, Shiying;  Zhao, Xiaoguang;  Tan, Min
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Semi-supervised anomaly detection  conditional variational auto-encoder  generative adversarial networks  informative manifold  structural similarity loss  
Development and validation of a novel MR imaging predictor of response to induction chemotherapy in locoregionally advanced nasopharyngeal cancer: a randomized controlled trial substudy (NCT01245959) 期刊论文
BMC Medicine, 2019, 卷号: 17, 期号: 1, 页码: 190
作者:  Dong,Di;  Zhang,Fan;  Zhong,Lian-Zhen;  Fang,Meng-Jie;  Huang,Cheng-Long;  Yao,Ji-Jin;  Sun,Ying;  Tian,Jie;  Ma,Jun;  Tang,Ling-Long
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Individualized imaging biomarker  Induction chemotherapy  Survival benefit  Treatment decision  Locoregionally advanced nasopharyngeal cancer  
Unsupervised Semantic-Based Aggregation of Deep Convolutional Features 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 2, 页码: 601-611
作者:  Xu, Jian;  Wang, Chunheng;  Qi, Chengzuo;  Shi, Cunzhao;  Xiao, Baihua
浏览  |  Adobe PDF(1963Kb)  |  收藏  |  浏览/下载:421/96  |  提交时间:2019/07/12
Unsupervised  semantic-based aggregation  semantic detectors  
Re-KISSME: A robust resampling scheme for distance metric learning in the presence of label noise 期刊论文
NEUROCOMPUTING, 2019, 卷号: 330, 期号: 22, 页码: 138-150
作者:  Zeng, Fanxia;  Zhang, Wensheng;  Zhang, Siheng;  Zheng, Nan
浏览  |  Adobe PDF(917Kb)  |  收藏  |  浏览/下载:428/71  |  提交时间:2019/07/12
Resampling scheme  KISSME  Distance metric learning  Label noise