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SSRN 2023年

作者： Li, Hongqing Jiang, Yunqing Zhang, Xiaoqiang Zhang, Fan Xiao, Yongguang Tang, Minghua Zhao, Zhenyang Xu, Yong Liu, Fengguang Zhao, Weisheng Beijing Advanced Innovation Center for Big Data and Brain Computing China School of Materials Science and Engineering Xiangtan University Hunan Xiangtan411105 China School of Integrated Circuit Science and Engineering Hefei Innovation Research Insititute Beihang University Beijing100191 China Anhui High Reliability Chips Engineering Laboratory Hefei230013 China Shandong Dongyi Photoelectric Instruments Co. Ltd Yantai264670 China Shandong Dongyi Institute of Optoelectronic Technology for Industry Yantai264670 China

Terahertz (THz) wave as an important electromagnetic wave has been increasingly applied in wireless communication and imaging sensing technology. It has been an increasingly practical application. Ultra-high data rates in communication technology push toward a broadband, controllable polarization, and multiple transmission channels signal sources. Here, we propose a programmable polarization spintronics terahertz source (PP-STS), in which contains a controllable polarization spintronic THz emitter and a microcontroller unit. The PP-STS not only can generate THz waves with wide frequency bandwidth, but also has the function of switching the orthogonal linear polarization state of the generated THz waves flexibly. By coding the microcontroller unit, the designed PP-SPS can directly program the orthogonal linear polarization states as a series of information to transmit. To achieve the interconversions between digital codes and the THz polarization information, an optimum matching THz polarization beam splitter (THz-PBS) is also designed via simulations and experiments. The THz-PBS, as a decoder, can accurately split the transverse electric (TE) and transverse magnetic (TM) modes into two THz detectors. At last, a coding and decoding prototype system of spintronic THz polarization is built by integrating the PP-STS, the THz-PBS and two THz detectors. The send and receive information with high speed and accuracy are verified in this prototype system as well. We believe that our work takes THz applications for multiplexing communications one step further and sheds light on commercializing the PP-STS with exciting manufacturing lines for efficient and economical THz polarization technology. © 2023, The Authors. All rights reserved.

关键词： Microcontrollers

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Spintronic Terahertz Polarization Programmable System for Information Encoding

SSRN

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SSRN 2023年

作者： Li, Hongqing Jiang, Yunqing Zhang, Xiaoqiang Zhang, Fan Xiao, Yongguang Tang, Minghua Zhao, Zhenyang Xu, Yong Liu, Fengguang Zhao, Weisheng School of Materials Science and Engineering Xiangtan University Hunan Xiangtan411105 China School of Integrated Circuit Science and Engineering Hefei Innovation Research Insititute Beihang University Beijing100191 China Anhui High Reliability Chips Engineering Laboratory Hefei230013 China Shandong Dongyi Photoelectric Instruments Co. Ltd Yantai264670 China Shandong Dongyi Institute of Optoelectronic Technology for Industry Yantai264670 China Beijing Advanced Innovation Center for Big Data and Brain Computing China

关键词： Microcontrollers

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Spintronic Terahertz Polarization Programmable System for Information Encoding

SSRN

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SSRN 2023年

关键词： Microcontrollers

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Spintronic Terahertz Polarization Programmable System for Information Encoding

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SSRN 2023年

关键词： Microcontrollers

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Predefined containment control for general linear multiagent systems with time-varying delays and switching topologies

Advanced Control for Applications: Engineering and Industria...

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Advanced Control for Applications: Engineering and Industrial Systems 2020年第2期2卷

作者： Zhou, Shiyu Hua, Yongzhao Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

Containment control problems for general linear multiagent systems with switching interaction topologies and time-varying delays are studied. Firstly, state observers are constructed to estimate the multiple leaders under the influence of switching graphs and time-varying delays. Secondly, a predefined containment protocol is presented based on the distributed state observer, where the expected convex combination of multiple leaders is predefined by several given weights. Moreover, an algorithm with two steps to confirm the gain matrices of the containment protocol and state observer is given. Based on linear matrix inequality technique and common Lyapunov-Krasovskii stability theory, the convergence of this control strategy for multiagent systems with switching topologies and time-varying delays to achieve state containment is proved. Finally, a numerical simulation is given to verify the validity of the theoretical results. © 2019 John Wiley & Sons, Ltd.

关键词： Multi agent systems

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Spintronic Terahertz Polarization Programmable System for Information Encoding

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SSRN 2023年

关键词： Microcontrollers

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Effects of Dynamic-Win-Stay-Lose-Learn model with voluntary participation in social dilemma

arXiv

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arXiv 2021年

作者： Shi, Zhenyu Wei, Wei Feng, Xiangnan Zhang, Ruizhi Zheng, Zhiming School of Mathematical Sciences Beihang University Beijing China Key Laboratory of Mathematics Informatics Behavioral Semantics Ministry of Education China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang China Peng Cheng Laboratory ShenzhenGuangdong China

In recent years, Win-Stay-Lose-Learn rule has attracted wide attention as an effective strategy updating rule, and voluntary participation is proposed by introducing a third strategy in Prisoner's dilemma game. Some researche show that combining Win-Stay-Lose-Learn rule with voluntary participation could promote cooperation mor significantly under moderate temptation values, however, cooperators' survival under high aspiration levels and high temptation values is still a challenging problem. In this paper, inspired by Achievement Motivation Theory a Dynamic-Win-Stay-Lose-Learn rule with voluntary participation is investigated, where a dynamic aspiration process is introduced to describe the co-evolution of individuals' strategies and aspirations. It is found tha cooperation is extremely promoted and defection is almost extinct in our model, even when the initial aspiration levels and temptation values are high. The combination of dynamic aspiration and voluntary participation play an active role since loners could survive under high initial aspiration levels and they will expand stably becaus of their fixed payoffs. The robustness of our model is also discussed and some adverse structures are found which should be alerted in the evolutionary process. Our work provides a more realistic model and shows tha cooperators may prevail defectors in an unfavorable initial environment. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

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Spintronic Terahertz Polarization Programmable System for Information Encoding

SSRN

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SSRN 2023年

关键词： Microcontrollers

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Spintronic Terahertz Polarization Programmable System for Information Encoding

SSRN

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SSRN 2023年

关键词： Microcontrollers

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Discriminative features matter: Multi-layer bilinear pooling for camera localization 30

Discriminative features matter: Multi-layer bilinear pooling...

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30th British Machine Vision Conference, BMVC 2019

作者： Wang, Xin Wang, Xiang Wang, Chen Bai, Xiao Wu, Jing Hancock, Edwin Robert School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Jiangxi Research Institute Beihang University Beijing China School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Department of Computer Science University of York York United Kingdom

Deep learning based camera localization from a single image has been explored recently since these methods are computationally efficient. However, existing methods only provide general global representations, from which an accurate pose estimation can not be reliably derived. We claim that effective feature representations for accurate pose estimation shall be both "informative" (focusing on geometrically meaningful regions) and "discriminative" (accounting for different poses of similar images). Therefore, we propose a novel multi-layer factorized bilinear pooling module for feature aggregation. Specifically, informative features are selected via bilinear pooling, and discriminative features are highlighted via multi-layer fusion. We develop a new network for camera localization using the proposed feature pooling module. The effectiveness of our approach is demonstrated by experiments on an outdoor Cambridge Landmarks dataset and an indoor 7 Scenes dataset. The results show that focusing on discriminative features significantly improves the network performance of camera localization in most cases. Codes will be available soon. © 2019. The copyright of this document resides with its authors.

关键词： Deep learning

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