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arXiv 2021年

作者： Huang, Chen He, Ruisi Ai, Bo Molisch, Andreas F. Lau, Buon Kiong Haneda, Katsuyuki Liu, Bo Wang, Cheng-Xiang Yang, Mi Oestges, Claude Zhong, Zhangdui The Purple Mountain Laboratories Nanjing211111 China The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China Peng Cheng Laboratory Shenzhen518055 China The Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States The Department of Electrical and Information Technology Lund University Lund22100 Sweden The Department of Radio Science and Engineering Aalto University Aalto00076 Finland The School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Purple Mountain Laboratories Nanjing211111 China The Institute of Information and Communication Technologies Electronics and Applied Mathematics Universite Catholique de Louvain Louvain-la-Neuve 1348 Belgium

To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques. In this two-part paper, we investigate the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. It firstly provides a comprehensive overview of ML for channel characterization and ML-based antenna-channel optimization in this first part, and then it gives a state-of-the-art literature review of channel scenario identification and channel modeling in Part II. Fundamental results and key concepts of ML for communication networks are presented, and widely used ML methods for channel data processing, propagation channel estimation, and characterization are analyzed and compared. A discussion of challenges and future research directions for ML-enabled next generation networks of the topics covered in this part rounds off the paper. © 2021, CC BY-NC-ND.

关键词： Machine learning

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Model-based joint bit allocation between geometry and color for video-based 3d point cloud compression

arXiv

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arXiv 2020年

作者： Liu, Qi Yuan, Hui Hou, Junhui Hamzaoui, Raouf Su, Honglei School of Information Science and Engineering Shandong University Qingdao266237 China Shenzhen Research Institute of Shandong University Shenzhen518057 China School of Control Science and Engineering Shandong University Ji’nan250061 China Department of Computer Science City University of Hong Kong Hong Kong School of Engineering and Sustainable Development De Montfort University Leicester United Kingdom School of Electronic Information Qingdao University Qingdao266071 China

Rate distortion optimization plays a very important role in image/video coding. But for 3D point cloud, this problem has not been investigated. In this paper, the rate and distortion characteristics of 3D point cloud are investigated in detail, and a typical and challenging rate distortion optimization problem is solved for 3D point cloud. Specifically, since the quality of the reconstructed 3D point cloud depends on both the geometry and color distortions, we first propose analytical rate and distortion models for the geometry and color information in video-based 3D point cloud compression platform, and then solve the joint bit allocation problem for geometry and color based on the derived models. To maximize the reconstructed quality of 3D point cloud, the bit allocation problem is formulated as a constrained optimization problem and solved by an interior point method. Experimental results show that the rate-distortion performance of the proposed solution is close to that obtained with exhaustive search but at only 0.68% of its time complexity. Moreover, the proposed rate and distortion models can also be used for the other rate-distortion optimization problems (such as prediction mode decision) and rate control technologies for 3D point cloud coding in the future. Copyright © 2020, The Authors. All rights reserved.

关键词： Signal distortion

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Research on the synergetic algorithm of linear permanent magnet motor

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Journal of computers (Taiwan) 2019年第3期30卷 231-242页

作者： Li, Jinzi Xiao, Jiongran Pan, Jianfei Department of Computer Engineering Shenzhen Polytechnic East Campus Administration Building 414 Shenzhen Guangdong518000 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen Guangdong518060 China

This paper studies the motion control system formed by three permanent magnet synchronous linear motors. In order to achieve the coordinated position control of the motors, the author first studies the influence of different communication topologies on the synergetic performance among motors;secondly, the author proposes an adjacent deviation coupled synergetic algorithm to improve the overall control effect of the synergetic system;lastly, the author designs and implements control experiment, the results of which indicate adjacent deviation coupled algorithm can effectively improve the synergetic accuracy among linear motors. Compared with traditional methods, the synergetic error among motors has declined from 0.3 mm to 0.25 mm and the synergetic accuracy has been improved by 17%. © 2019 computer Society of the Republic of China. All rights reserved.

关键词： Linear motors

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3D Visualization of Objects under scattering media conditions using Integral Imaging

3D Visualization of Objects under scattering media condition...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Jaehoon Lee Kotaro Inoue Myungjin Cho Min-Chul Lee Department of Computer Science and Networks Kyushu Institute of Technology Iizuka city Japan Electrical Electronic and Control Engineering Hankyong National University Anseong-si Korea

In this paper, we propose a new three-dimensional (3D) reconstruction technique in scattering media using integral imaging. In conventional integral imaging, it can visualize 3D images well when high-resolution elemental images are used. However, when low-resolution images are used, the visual quality of the 3D images is reduced. In addition, it is difficult to recognize the objects under scattering media conditions. Therefore, to visualize 3D images in scattering media, we create a mask filter in frequency domain to remove the scattering media. In addition, we calculate the density of the scattered media to adjust the contrast and histogram equalization automatically. To prove our method, we implemented optical experiments.

关键词： Media Scattering Three-dimensional displays Image reconstruction Imaging Visualization Histograms

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Path planning for autonomous bus driving in urban environments

arXiv

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arXiv 2019年

作者： Oliveira, Rui Lima, Pedro F. Pereira, Goncalo Collares Martensson, Jonas Wahlberg, Bo Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Scania Autonomous Transport Solutions Sodertalje Sweden

Driving in urban environments often presents difficult situations that require expert maneuvering of a vehicle. These situations become even more challenging when considering large vehicles, such as buses. We present a path planning framework that addresses the demanding driving task of buses in urban areas. The approach is formulated as an optimization problem using the road-aligned vehicle model. The road-aligned frame introduces a distortion on the vehicle body and obstacles, motivating the development of novel approximations that capture this distortion. These approximations allow for the formulation of safe and nonconservative collision avoidance constraints. Unlike other path planning approaches, our method exploits curbs and other sweepable regions, which a bus must often sweep over in order to manage certain maneuvers. Furthermore, it takes full advantage of the particular characteristics of buses, namely the overhangs, an elevated part of the vehicle chassis, that can sweep over curbs. Simulations are presented, showing the applicability and benefits of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Motion planning

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Convex Relaxation with Log-Determinant Divergence-L1 Regularization for 3D Shape Reconstruction

Convex Relaxation with Log-Determinant Divergence-L1 Regular...

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第三十八届中国控制会议

作者： Wei Cao Luefeng Chen Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta

Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape with LDD-L1 regularization,which is the construction of the shape space model. Based on the proposed convex optimization method, 3 D human pose reconstruction by shape space model and 3 D variable shape model was carried out on the mocap database. To improve accuracy and reduce the number of iterations, we use PSO algorithm to optimize initial value of the key parameter. The experimental results show that the improved algorithm exhibits less iterations but higher accuracy, which can be much helpful in practical applications.

关键词： LDD-L1 regularization 3D reconstruction PSO

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A pre-allocation design for cost minimization and delay constraint in vehicular offloading system

arXiv

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arXiv 2019年

作者： Chen, Zhijie Yang, Bo Chen, Cailian Guan, Xinping Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China China

To accommodate exponentially increasing traffic demands of vehicle-based applications, operators are utilizing offloading as a promising technique to improve quality of service (QoS), which gives rise to the application of Mobile Edge Computing (MEC). While the conventional offloading paradigms focus on delay and energy tradeoff, they either fail to find efficient models to represent delay, especially the queueing delay, or underestimate the role of MEC Server. In this paper, we propose a novel Pre-Allocation Design for vehicular Offloading (PADO). A task delay queue is constructed based on an allocate-execute separate (AES) mechanism. Due to the dynamics of vehicular network, we are inspired to utilize Lyapunov optimization to minimize the execution cost of each vehicle and guarantee task delay. The MEC Server with energy harvesting devices is also taken into consideration of the system. The transaction between vehicles and server is decided by a Stackelberg Game framework. We conduct extensive experiments to show the property and superiority of our proposed framework. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy harvesting

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Secure Distributed Filtering for Unstable Dynamics Under Compromised Observations

Secure Distributed Filtering for Unstable Dynamics Under Com...

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IEEE Annual Conference on Decision and control

作者： Xingkang He Xiaoqiang Ren Henrik Sandberg Karl H. Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Automation Shanghai University Shanghai China

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

In this paper, we consider a secure distributed filtering problem for linear time-invariant systems with bounded noises and unstable dynamics under compromised observations. A malicious attacker is able to compromise a subset of the agents and manipulate the observations arbitrarily. We first propose a recursive distributed filter consisting of two parts at each time. The first part employs a saturation-like scheme, which gives a small gain if the innovation is too large. The second part is a consensus operation of state estimates among neighboring agents. A sufficient condition is then established for the boundedness of estimation error, which is with respect to network topology, system structure, and the maximal compromised agent subset. We further provide an equivalent statement, which connects to 2s-sparse observability in the centralized framework in certain scenarios, such that the sufficient condition is feasible. Numerical simulations are finally provided to illustrate the developed results.

关键词： Observability Estimation error Technological innovation control systems State estimation Robustness

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Neuro-Adaptive Learning Approach for Predicting Production Performance and Pressure Dynamics of Gas Condensation Reservoir

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IFAC-PapersOnLine 2019年第29期52卷 122-127页

作者： Aliyuda Ali Lingzhong Guo Department of Automatic Control and Systems Engineering University of Sheffield Sheffield. S10 2TN UK Department of Mathematics and Computer Science Gombe State University P.M.B. 127 Gombe Nigeria

In Reservoir engineering, state-of-the-art data analysis enables engineers to characterize reservoirs and plan for developing fields. This allows production companies to save huge amounts that would otherwise be allocated to reservoir modelling and simulation and well testing. Numerical reservoir modelling and simulation is the standard use in industries today for comprehensive study of fields. However, the inflexible behaviour, development time and cost of numerical simulators are major challenges to production engineers, managers as well as modellers. On the other hand, Artificial Intelligence (AI) based reservoir models are characterised with low cost of development, short development time and fast tract analysis and flexibility to estimate the uncertainties normally found in numerical simulators. In this study, a strategy for controlling gas production and pressure drop in gas condensate reservoir is described. Numerical simulations of production rate and pressure drop were carried out first and their results were saved. An Adaptive Neuro-Fuzzy system was then developed and trained with some parts of the numerical simulation results. This AI-based system is checked and tested with part of the numerical simulation results that had not been used during the training. The developed system regenerates the numerical simulation results for both production rates and pressure drop at different Bottom Hole Pressures (BHPs) with very high accuracy (>98%). Results of this study showed that AI-based reservoir simulation can be considered a vital tool of help to production engineers, managers and modellers for a quick and more informed decision as regards field development plans that can meet operational targets.

关键词： Gas condensate reservoirs Neuro-Adaptive Learning System Bottom-Hole Pressure

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Time-Varying Convex Optimization: Time-Structured Algorithms and Applications

arXiv

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arXiv 2020年

作者： Simonetto, Andrea Dall’Anese, Emiliano Paternain, Santiago Leus, Geert Giannakis, Georgios B. Optimization and Control Group of IBM Research Ireland Dublin Ireland College of Engineering and Applied Science University of Colorado BoulderCO80309 United States Department of Electrical and Systems Engineering University of Pennsylvania Faculty of Electrical Mathematics and Computer Science Delft University of Technology Delft2628CD Netherlands Digital Technology Center University of Minnesota MinneapolisMN55455 United States

Optimization underpins many of the challenges that science and technology face on a daily basis. Recent years have witnessed a major shift from traditional optimization paradigms grounded on batch algorithms for medium-scale problems to challenging dynamic, time-varying, and even huge-size settings. This is driven by technological transformations that converted infrastructural and social platforms into complex and dynamic networked systems with even pervasive sensing and computing capabilities. The present paper reviews a broad class of state-of-the-art algorithms for time-varying optimization, with an eye to both algorithmic development and performance analysis. It offers a comprehensive overview of available tools and methods, and unveils open challenges in application domains of broad interest. The real-world examples presented include smart power systems, robotics, machine learning, and data analytics, highlighting domain-specific issues and solutions. The ultimate goal is to exempify wide engineering relevance of analytical tools and pertinent theoretical foundations. Copyright © 2020, The Authors. All rights reserved.

关键词： Data Analytics

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