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Cooperative Target Fencing of Multiple Vehicles for a General Target with Connectivity Preservation and Collision Avoidance

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Journal of Systems Science & Complexity 2024年第1期37卷 136-151页

作者： PAN Zini CHEN Ben M department of Mechanical and Automation engineering The Chinese University of Hong KongHong KongChina

In this paper,the authors study the cooperative target-fencing problem for n-dimensional systems and a target with a general *** using the velocity of the vehicles,a position feedback control law is proposed to fence the general target into the convex hull formed by the ***,the dynamics of each vehicle is described by a double-integrator *** potential functions are designed to guarantee connectivity preservation of the communication network and collision avoidance among the *** proposed approach can deal with a target whose trajectory is any twice continuously differentiable function of *** effectiveness of the result is verified by a numerical example.

关键词： Multi-agent systems networked systems target fencing

Monolithic integrated optoelectronic chip for vector force detection

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Microsystems & Nanoengineering 2024年第3期10卷 245-257页

作者： Jiansong Feng Zhongqi Wang Mengyuan Zhanghu Xu Zhang Yong Shen Jing Yang Zhibin Li Bin Chen Taihong Wang Xiaolong Chen Zhaojun Liu department of Electrical and electronic engineering Southern University of Science and TechnologyShenzhen 518055China department of Electrical and electronic engineering The University of Hong KongHong KongChina

Sensors with a small footprint and real-time detection capabilities are crucial in robotic surgery and smart wearable *** device footprint while maintaining its high performance is a major challenge and a significant limitation to their ***,we proposed a monolithic integrated micro-scale sensor,which can be used for vector force *** sensor combines an optical source,four photodetectors,and a hemispherical silicone elastomer component on the same sapphire-based AlGaInP *** chip-scale optical coupling is achieved by employing the laser lift-off techniques and the flip-chip bonding to a processed sapphire *** hemispherical structure device can detect normal and shear forces as low as 1mN within a measurement range of 0–220 mN for normal force and 0–15 mN for shear *** packaging,the sensor is capable of detecting forces over a broader range,with measurement capabilities extending up to 10 N for normal forces and 0.2 N for shear *** has an accuracy of detecting a minimum normal force of 25 mN and a minimum shear force of 20 ***,this sensor has been validated to have a compact footprint of approximately 1.5 mm^(2),while maintaining high real-time *** also demonstrate its promising potential by combining this sensor with fine surface texture perception in the fields of compact medical robot interaction and wearable devices.

关键词： robot force smart

Distributed Nash Equilibrium Seeking on Compact Action Sets over Jointly Strongly Connected Switching Networks

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Journal of Systems Science & Complexity 2024年第1期37卷 63-81页

作者： HE Xiongnan HUANG Jie department of Mechanical and Automation engineering The Chinese University of Hong KongHong Kong 999077China.

This paper studies the distributed Nash equilibrium seeking(DNES)problem for games whose action sets are compact and whose network graph is switching satisfying the jointly strongly connected *** keep the actions of all players in their action sets all the time,one has to resort to the projected gradient-based *** the assumption that the unique Nash equilibrium is the unique equilibrium of the pseudogradient system,an algorithm is proposed that is able to exponentially find the Nash ***,the authors also consider the distributed Nash equilibrium seeking problem for games whose actions are governed by high-order integrator dynamics and belong to some compact *** examples are used to illustrate the proposed approach.

关键词： Compact action sets jointly strongly connected switching graphs Nash equilibrium seeking projected gradient-based algorithm.

Data-driven Static Equivalence with Physics-informed Koopman Operators

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 432-438页

作者： Wei Lin Changhong Zhao Maosheng Gao C.Y.Chung department of Electrical engineering The Hong Kong Polytechnic UniversityHong Kong SARChina department of Information engineering The Chinese University of Hong KongHong Kong SARChina School of Electrical engineering Chongqing UniversityChongqing 400044China

With deployment of measurement units,fitting static equivalent models of distribution networks(DNs)by linear regression has been recognized as an effective method in power flow analysis of a transmission *** volatility of measurements caused by variable distributed renewable energy sources makes it more difficult to accurately fit such equivalent *** tackle this challenge,this letter proposes a novel data-driven method to improve equivalency accuracy of DNs with distributed energy *** letter provides a new perspective that an equivalent model can be regarded as a mapping from internal conditions and border voltages to border power *** mapping can be established through 1)Koopman operator theory,and 2)physical features of power flow equations at the root node of a *** of the proposed method is demonstrated on the IEEE 33-bus and IEEE 136-bus test systems connected to a 661-bus utility system.

关键词： Data-driven distribution network Koopman operator theory static equivalent model

More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 622-637页

作者： Han Xu Jiayi Ma Yixuan Yuan Hao Zhang Xin Tian Xiaojie Guo the electronic Information School Wuhan UniversityWuhan 430072China IEEE the department of electronic engineering Chinese University of Hong KongHong Kong 999077China the College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of *** enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is *** contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better *** self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and *** response,this paper proposes a self-supervised enhancement method,termed as *** can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised *** attenuation is estimated based on physical principles and local neighborhood *** removal and correction of noise and color shift removal are solely realized with noisy images and images with color ***,the comprehensive and fully self-supervised approach can achieve better adaptability and *** is applicable to various low light conditions,and can reproduce the original color of scenes in natural *** experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art *** code is available at https://***/hanna-xu/SLIE.

关键词： Color correction low-light image enhancement self-supervised learning.

Light-based 3D printing of stimulus-responsive hydrogels forminiature devices:recent progress and perspective

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Bio-Design and Manufacturing 2024年第5期7卷 721-746页

作者： Chen Xin Neng Xia Li Zhang department of Mechanical and Automation engineering The Chinese University of Hong KongHong Kong 999077China Multi-Scale Medical Robotics Center Hong Kong Science ParkShatin NTHong Kong 999077China Chow Yuk Ho Technology Center for Innovative Medicine The Chinese University of Hong KongHong Kong 999077China department of Surgery The Chinese University of Hong KongHong Kong 999077China CUHK T Stone Robotics Institute The Chinese University of Hong KongHong Kong 999077China

Miniature devices comprising stimulus-responsive hydrogels with high environmental adaptability are now considered competitive candidates in the fields of biomedicine,precise sensors,and tunable *** and advanced fabricationmethods are critical formaximizing the application capabilities ofminiature ***-based three-dimensional(3D)printing technology offers the advantages of a wide range of applicable materials,high processing accuracy,and strong 3D fabrication capability,which is suitable for the development of miniature devices with various *** paper summarizes and highlights the recent advances in light-based 3D-printed miniaturized devices,with a focus on the latest breakthroughs in lightbased fabrication technologies,smart stimulus-responsive hydrogels,and tunable miniature devices for the fields of miniature cargo manipulation,targeted drug and cell delivery,active scaffolds,environmental sensing,and optical ***,the challenges in the transition of tunable miniaturized devices from the laboratory to practical engineering applications are *** opportunities that will promote the development of tunable microdevices are elaborated,contributing to their improved understanding of these miniature devices and further realizing their practical applications in various fields.

关键词： 3D printing Stimulus-responsive hydrogels Miniature devices Shape-morphing

WirelessLLM:Empowering Large Language Models Towards Wireless Intelligence

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Journal of Communications and Information Networks 2024年第2期9卷 99-112页

作者： Jiawei Shao Jingwen Tong Qiong Wu Wei Guo Zijian Li Zehong Lin Jun Zhang department of electronic and Computer engineering The Hong Kong University of Science and TechnologyHong Kong 999077China

The rapid evolution of wireless technologies and the growing complexity of network infrastructures necessitate a paradigm shift in how communication networks are designed,configured,and managed. Recent advancements in large language models (LLMs) have sparked interest in their potential to revolutionize wireless communication systems. However, existing studies on LLMs for wireless systems are limited to a direct application for telecom language understanding. To empower LLMs with knowledge and expertise in the wireless domain, this paper proposes WirelessLLM, a comprehensive framework for adapting and enhancing LLMs to address the unique challenges and requirements of wireless communication networks. We first identify three foundational principles that underpin WirelessLLM:knowledge alignment, knowledge fusion, and knowledge evolution. Then,we investigate the enabling technologies to build WirelessLLM, including prompt engineering, retrieval augmented generation, tool usage, multi-modal pre-training, and domain-specific fine-tuning. Moreover, we present three case studies to demonstrate the practical applicability and benefits of WirelessLLM for solving typical problems in wireless networks. Finally, we conclude this paper by highlighting key challenges and outlining potential avenues for future research.

关键词： large language models multi-modal models wireless communications power allocation spectrum sensing protocol understanding

On the use of deep learning for phase recovery

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Light(Science & Applications) 2024年第2期13卷 190-235页

作者： Kaiqiang Wang Li Song Chutian Wang Zhenbo Ren Guangyuan Zhao Jiazhen Dou Jianglei Di George Barbastathis Renjie Zhou Jianlin Zhao Edmund Y.Lam department of Electrical and electronic engineering The University of Hong KongHong Kong SARChina School of Physical Science and Technology Northwestern Polytechnical UniversityXi’anChina department of Biomedical engineering The Chinese University of Hong KongHong Kong SARChina School of Information engineering Guangdong University of TechnologyGuangzhouChina department of Mechanical engineering Massachusetts Institute of TechnologyCambridgeMAUSA

Phase recovery(PR)refers to calculating the phase of the light field from its intensity *** exemplified from quantitative phase imaging and coherent diffraction imaging to adaptive optics,PR is essential for reconstructing the refractive index distribution or topography of an object and correcting the aberration of an imaging *** recent years,deep learning(DL),often implemented through deep neural networks,has provided unprecedented support for computational imaging,leading to more efficient solutions for various PR *** this review,we first briefly introduce conventional methods for ***,we review how DL provides support for PR from the following three stages,namely,pre-processing,in-processing,and *** also review how DL is used in phase image ***,we summarize the work in DL for PR and provide an outlook on how to better use DL to improve the reliability and efficiency of ***,we present a live-updating resource(https://***/kqwang/phase-recovery)for readers to learn more about PR.

关键词： networks phase optics

MAUN:Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1139-1150页

作者： Qian Hu Jiayi Ma Yuan Gao Junjun Jiang Yixuan Yuan electronic Information School Wuhan UniversityWuhan 430072China School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China department of electronic engineering Chinese University of Hong KongHong Kong 999077China

Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D *** algorithm for restoring the original 3D hyperspectral images(HSIs)from compressive measurements is pivotal in the imaging *** approaches painstakingly designed networks to directly map compressive measurements to HSIs,resulting in the lack of interpretability without exploiting the imaging *** some recent works have introduced the deep unfolding framework for explainable reconstruction,the performance of these methods is still limited by the weak information transmission between iterative *** this paper,we propose a Memory-Augmented deep Unfolding Network,termed MAUN,for explainable and accurate HSI ***,MAUN implements a novel CNN scheme to facilitate a better extrapolation step of the fast iterative shrinkage-thresholding algorithm,introducing an extra momentum incorporation step for each iteration to alleviate the information ***,to exploit the high correlation of intermediate images from neighboring iterations,we customize a cross-stage transformer(CSFormer)as the deep denoiser to simultaneously capture self-similarity from both in-stage and cross-stage features,which is the first attempt to model the long-distance dependencies between iteration *** experiments demonstrate that the proposed MAUN is superior to other state-of-the-art methods both visually and *** code is publicly available at https://***/HuQ1an/MAUN.

关键词： Deep folding iteration