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检索条件"机构=Center for Control Engineering and Computation Electrical and Computer Engineering Department"
1954 条 记 录,以下是161-170 订阅
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Switching between topological edge states using phase-change materials
Switching between topological edge states using phase-change...
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2023 Active Photonic Platforms, APP 2023
作者: Veronis, Georgios Huang, Yin Shen, Yuecheng School of Electrical Engineering and Computer Science Louisiana State University Baton RougeLA70803 United States Center for Computation and Technology Louisiana State University Baton RougeLA70803 United States Department of Optoelectrics Information Science and Engineering School of Physics and Electronics Central South University Hunan Changsha410012 China State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-Sen University Guangdong Guangzhou510275 China
We introduce non-Hermitian plasmonic waveguide-cavity structures based on the Aubry-Andre-Harper model to realize switching between right and left topological edge states using the phase-change material germanium-anti... 详细信息
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Dual-beam photothermal material trace detection method based on self-mixing interference
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Applied Optics 2025年 第16期64卷 4549-4558页
作者: Yan Zhao Yunlong Zhi Hui Zhao Daming Dong Jigang Tong Chunling Tu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria 0188 South Africa
In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod exc... 详细信息
来源: 评论
Discrete-Time Distributed Optimization for Linear Uncertain Multi-Agent Systems
Discrete-Time Distributed Optimization for Linear Uncertain ...
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IEEE Conference on Decision and control
作者: Tong Liu Michelangelo Bin Ivano Notarnicola Thomas Parisini Zhong-Ping Jiang Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn NY USA Department of Electrical Electronic and Information Engineering University of Bologna Bologna Italy Department of Electrical and Electronic Engineering Imperial College London London UK Department of Engineering and Architecture University of Trieste Trieste Italy KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus
The distributed optimization algorithm proposed by J. Wang and N. Elia in 2010 has been shown to achieve linear convergence for multi-agent systems with single-integrator dynamics. This paper extends their result, inc...
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High-Value Target Escort and Defense Scenario with Differential Subgame Cost
High-Value Target Escort and Defense Scenario with Different...
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IEEE Conference on Decision and control
作者: Rachael L. Judy Zachariah E. Fuchs David W. Casbeer Department of Electrical Engineering and Computer Science University of Cincinnati Cincinnati OH Control Science Center of Excellence Air Force Research Laboratory 2210 8th St. WPAFB OH
An Escort and Defense Scenario is presented in which a high-value Target maneuvers through a high-risk region while being escorted by a mobile, defensive agent. Along this trajectory, an Attacker may be launched from ... 详细信息
来源: 评论
Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT Networks
arXiv
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arXiv 2025年
作者: Yang, Xiaohong Liwang, Minghui Fu, Liqun Su, Yuhan Hosseinalipour, Seyyedali Wang, Xianbin Hong, Yiguang School of Informatics Xiamen University Fujian China Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China School of Electronic Science and Engineering Xiamen University Xiamen China Department of Electrical Engineering University at Buffalo-SUNY BuffaloNY United States Department of Electrical and Computer Engineering Western University ON Canada
Hierarchical Federated Learning (HFL) introduces intermediate aggregation layers, addressing the limitations of conventional Federated Learning (FL) in geographically dispersed environments with limited communication ... 详细信息
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Mining Erasable Patterns Using the Bitmap Method in Quantitative Component Databases  17th
Mining Erasable Patterns Using the Bitmap Method in Quantita...
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17th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2025
作者: Hong, Tzung-Pei Chen, Da Huang, Wei-Ming Tsai, Yu-Chuan Department of Computer Science and Information Engineering National University of Kaohsiung Kaohsiung City Taiwan Department of Electrical and Control China Steel Corporation Kaohsiung City Taiwan Library and Information Center National University of Kaohsiung Kaohsiung City Taiwan
Mining erasable patterns from a database are for applying resources to maximize production with limited funds. Since the concept of erasable pattern mining was proposed, a manager can use it to optimize the production... 详细信息
来源: 评论
Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach
arXiv
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arXiv 2022年
作者: Jafarpour, Saber Davydov, Alexander Abate, Matthew Bullo, Francesco Coogan, Samuel School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta United States Center for Control Dynamical Systems and Computation University of California Santa Barbara United States
This paper proposes a theoretical and computational framework for training and robustness verification of implicit neural networks based upon non-Euclidean contraction theory. The basic idea is to cast the robustness ... 详细信息
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Risk-Sensitive Inhibitory control for Safe Reinforcement Learning
Risk-Sensitive Inhibitory Control for Safe Reinforcement Lea...
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IEEE Conference on Decision and control
作者: Armin Lederer Erfaun Noorani John S. Baras Sandra Hirche Chair of Information-oriented Control (ITR) School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical and Computer Engineering Institute for Systems Research (ISR) at the University of Maryland College Park MD USA
Humans have the ability to deviate from their natural behavior when necessary, which is a cognitive process called response inhibition. Similar approaches have independently received increasing attention in recent yea...
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State Derivative Normalization for Continuous-Time Deep Neural Networks
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IFAC-PapersOnLine 2024年 第15期58卷 253-258页
作者: Jonas Weigand Gerben I. Beintema Jonas Ulmen Daniel Görges Roland Tóth Maarten Schoukens Martin Ruskowski Chair of Machine Tools and Control Systems RPTU Kaiserslautern and the German Research Center for Artificial Intelligence Kaiserslautern Germany Control Systems (CS) Group at the Department of Electrical Engineering Eindhoven University of Technology Netherlands. R. Tóth is also affiliated to the Systems and Control Laboratory at the Institute for Computer Science and Control Budapest Hungary Institute for Electromobility RPTU Kaiserslautern Germany
The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state... 详细信息
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A Continuous Off-Policy Reinforcement Learning Scheme for Optimal Motion Planning in Simply-Connected Workspaces
A Continuous Off-Policy Reinforcement Learning Scheme for Op...
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras Center of AI & Robotics (CAIR) New York University Abu Dhabi
In this work, an Integral Reinforcement Learning (RL) framework is employed to provide provably safe, convergent and almost globally optimal policies in a novel Off-Policy Iterative method for simply-connected workspa...
来源: 评论