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检索条件"机构=The Key Laboratory of System Control and Information Processing"
5610 条 记 录,以下是3881-3890 订阅
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Battle damage assessment based on an improved Kullback-Leibler divergence sparse autoencoder
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Frontiers of information Technology & Electronic Engineering 2017年 第12期18卷 1991-2000页
作者: Zong-feng QI Qiao-qiao LIU Jun WANG Jian-xun LI State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Luoyang 471003 China MOE Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China Luoyang Electronic Equipment Test Center of China Luoyang 471000 China
The nodes number of the hidden layer in a deep learning network is quite difficult to determine with traditional methods. To solve this problem, an improved Kullback-Leibler divergence sparse autoencoder (KL-SAE) is... 详细信息
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A Feature Matching Method For Simultaneous Localization And Mapping  2
A Feature Matching Method For Simultaneous Localization And ...
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2017 IEEE 2nd information Technology, Networking, Electronic and Automation control Conference (ITNEC 2017)
作者: Chen Xiangkui Jiang Min Zuo Liangyu Jiang jian College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System
Simultaneous Localization and Mapping is an important technology which help a mobile robot to determine its location and build the environment map. Recently, the RGBD sensor is widely used in the robot, research on RG... 详细信息
来源: 评论
Toward stronger robustness of network controllability: A snapback network model
arXiv
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arXiv 2018年
作者: Lou, Yang Wang, Lin Chen, Guanrong Department of Electronic Engineering City University of Hong Kong Hong Kong SAR Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China
A new complex network model, called q-snapback network, is introduced. Basic topological characteristics of the network, such as degree distribution, average path length, clustering coefficient and Pearson correlation... 详细信息
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A high-precision vision-based mobile robot slope detection method in unknown environment
A high-precision vision-based mobile robot slope detection m...
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Chinese Automation Congress
作者: Kenan Du Jing Xin Yaqian Shi Ding Liu Youmin Zhang CETC 20 Shaanxi key Laboratory of Integrated and Intelligent Navigation Xi'an P.R. China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi‘an University of Technology Xi'an P.R. China Department of Mechanical and Industrial Engineering Concordia University Quebec Canada
Aiming at satisfying the demand of slope perception accuracy for mobile robots in the unknown environment, a high-precision vision-based mobile robot slope detection method in unknown environment is proposed in this p... 详细信息
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ANISOTROPIC SCATTERING DETECTION FOR CHARACTERIZING POLARIMETRIC CIRCULAR SAR MULTI-ASPECT SIGNATURES
ANISOTROPIC SCATTERING DETECTION FOR CHARACTERIZING POLARIME...
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IEEE International Geoscience and Remote Sensing Symposium
作者: Yang Li Yun Lin Wen Hong Ran Xu Zhimin Zhuo Qiang Yin Beijing Institute of Electronic System Engineering Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Science Beijing China Beijing University of Chemical Technology Beijing China
Circular synthetic aperture radar (CSAR) can provide distinctive multi-aspect anisotropic scattering signatures. However, it is impossible to retain the anisotropic signatures in a SAR image that combines all the suba... 详细信息
来源: 评论
Reliability analysis and matpower simulation of IEEE14 node based on mixed entropy measure
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European Journal of Electrical Engineering 2018年 第5-6期20卷 573-588页
作者: Shao, Zhenhua Zhong, Zhixiong Lin, Wenzhong China Digital Fujian IoT Laboratory of Intelligent Production Minjiang University Fujian350108 China Fujian Province Key Laboratory of Information Processing and Intelligent Control Minjiang University Fujian350108 China College of Computer and Control Engineering Minjiang University Fujian350108 China
With the increasingly large-scale interconnection of power system, the object of this paper was to analyze the fragility of the fault of IEEE14 nodes based on the mixed entropy *** mixed entropy approach was adopted t... 详细信息
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Chain Recurrent Point and Devaney Chaos of Topological Groups
Chain Recurrent Point and Devaney Chaos of Topological Group...
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International Conference on Smart City and systems Engineering
作者: JI Zhanjiang QIN Guijiang ZHAI Cong Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University China School of Transportation and Civil Engineering and Architecture Fo Shan University China
Chain recurrent point, strong chain recurrent point and Devaney chaos have an important significance in terms of theory and application. In this paper, we will introduce the concept of chain recurrent point, strong ch... 详细信息
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Multiple Kernel Learning for Representation-based Classification of Hyperspectral Images
Multiple Kernel Learning for Representation-based Classifica...
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第30届中国控制与决策会议
作者: Yu Qin Xiaoyong Bian Yuxia Sheng School of Computer Science Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Information Science and Engineenring Wuhan University of Science and Technology
In the paper we propose a multiple kernel learning framework for representation-based classification(MKLC) of hyperspectral images. Unlike the existing methods that often exploit the single feature extraction method... 详细信息
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Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic (vol 11, 5172, 2020)
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NATURE COMMUNICATIONS 2020年 第1期11卷 5172页
作者: Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu Zhu, Biqing Guo, Rui Ke, Piyu Sun, Taochun Lu, Chenxi He, Pan Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Tanaka, Katsumasa Wei, Yiming Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Liu, Miaomiao Breon, Francois-Marie Lu, Yonglong Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of Earth System Science Tsinghua University Beijing China. zhuliu@***. Laboratoire des Sciences du Climat et de l'Environnement LSCE CEA CNRS UVSQ Centre d'Etudes Orme de Merisiers Gif-sur-Yvette France. Department of Earth System Science Tsinghua University Beijing China. Department of Meteorology and Atmospheric Science The Pennsylvania State University University Park PA USA. Department of Earth System Science University of California Irvine 3232 Croul Hall Irvine CA USA. Division of Geological and Planetary Sciences California Institute of Technology Pasadena CA USA. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology Nanjing China. Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China. Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. School of Environment Tsinghua University Beijing China. School of Mathematical School Tsinghua University Beijing China. Department of Mathematical Sciences Tsinghua University Beijing China. Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China. Institut Pierre-Simon Laplace Sorbonne Université / CNRS Paris France. Université Paris Dauphine Place du Maréchal de Lattre de Tassigny 75016 Paris France. Center for Energy and Environmental Policy Research Beijing Institute of Technology Beijing China. Department of Electrical Engineering the State Key Lab of Control and Simulation of Power Systems and Generation Equipment Institute for National Governance and G
A Correction to this paper has been published: https://***/10.1038/s41467-020-20254-5
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Preventive Soot Blowing Strategy based on State of Health Prediction for Coal-fired Power Plant Boiler
Preventive Soot Blowing Strategy based on State of Health Pr...
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第37届中国控制会议
作者: Yuanhao Shi Jie Wen Xiaoqiong Pang Jianfang Jia Fangshu Cui Jianchao Zeng Jingcheng Wang North University of China School of Electrical and Control Engineering North University of China School of Computer Science and Technology North University of ChinaSchool of Computer Science and Technology Shanghai Jiao Tong University Department of Automationand Key Laboratory of System Control and Information ProcessingMinistry of Education of China
This paper seeks the optimization of soot-blowing operations for heat transfer surfaces in coal-fired power plant boiler.A preventive soot blowing strategy based on state of health prediction for heat transfer surface... 详细信息
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