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arXiv 2017年

作者： Charalambous, Themistoklis Kim, Su Min Nomikos, Nikolaos Bengtsson, Mats Johansson, Mikael Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Electronics Engineering Korea Polytechnic University Siheung Korea Republic of Department of Information and Communication Systems Engineering University of the Aegean Samos Greece Department of Information Science and Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

We study a cooperative network with a buffer-aided multi-antenna source, multiple half-duplex (HD) buffer-aided relays and a single destination. Such a setup could represent a cellular downlink scenario, in which the source can be a more powerful wireless device with a buffer and multiple antennas, while a set of intermediate less powerful devices are used as relays to reach the destination. The main target is to recover the multiplexing loss of the network by having the source and a relay to simultaneously transmit their information to another relay and the destination, respectively. Successive transmissions in such a cooperative network, however, cause inter-relay interference (IRI). First, by assuming global channel state information (CSI), we show that the detrimental effect of IRI can be alleviated by precoding at the source, mitigating or even fully cancelling the interference. A cooperative relaying policy is proposed that employs a joint precoding design and relay-pair selection. Note that both fixed rate and adaptive rate transmissions can be considered. For the case when channel state information is only available at the receiver side (CSIR), we propose a relay selection policy that employs a phase alignment technique to reduce the IRI. The performance of the two proposed relay pair selection policies are evaluated and compared with other state-of-the-art relaying schemes in terms of outage and throughput. The results show that the use of a powerful source can provide considerable performance improvements. Copyright © 2017, The Authors. All rights reserved.

关键词： Channel state information

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Integrating semi-supervised label propagation and random forests for multi-atlas based hippocampus segmentation

arXiv

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arXiv 2017年

作者： Zheng, Qiang Fan, Yong Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States School of Computer and Control Engineering Yantai University Yantai264005 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China

A novel multi-atlas based image segmentation method is proposed by integrating a semi-supervised label propagation method and a supervised random forests method in a pattern recognition based label fusion framework. The semi-supervised label propagation method takes into consideration local and global image appearance of images to be segmented and segments the images by propagating reliable segmentation results obtained by the supervised random forests method. Particularly, the random forests method is used to train a regression model based on image patches of atlas images for each voxel of the images to be segmented. The regression model is used to obtain reliable segmentation results to guide the label propagation for the segmentation. The proposed method has been compared with state-of-the-art multi-atlas based image segmentation methods for segmenting the hippocampus in MR images. The experiment results have demonstrated that our method obtained superior segmentation performance. Copyright © 2017, The Authors. All rights reserved.

关键词： Image segmentation

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Reliability & security issues for IoT-based smart business center: Architecture & Markov model 3

Reliability & security issues for IoT-based smart business c...

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3rd International Conference on Mathematics and computers in Sciences and in Industry, MCSI 2016

作者： Kharchenko, Vyacheslav Kolisnyk, Maryna Piskachova, Iryna Bardis, Nikolaos Department of Computer Systems and Networks National Aerospace University KhAI Kharkiv Ukraine Department of Automation and Control in Technical Systems National Technical University KPI Kharkiv Ukraine Department of Computer Science and Control System Ukrainian State University of Railway Transport Kharkiv Ukraine Department of Mathematics and Engineering Sciences Hellenic Military Academy Athens Vari16673 Greece

ISBN: (纸本)9781509009732

One of the key subsystems from point of view of security of the complex IoT system is the smart business center (SB?) system. Some problems the design and operation of the SBC system are analyzed. When analysis of safety of the IoT system must take into account the reliability and security of the system at several levels: The level of sensors, the level of communication (communication lines, router, switch), the server level as the control device of components of the network, the level of the entire SBC subsystem. General architecture of network of the SB? is described. Reliability and security of key SB? hardwareand software manufacturers are analysed. In particular, security issue for SB? routers is considered. Shown the Markov model, which takes into account the technical conditions of typical network components of the SBC with the presence of software vulnerabilities when exposed to hacker attacks. On this model's basis it is possible to conduct further researches directed for improving the reliability operation and safety of IoT. ©2016 IEEE.

关键词： Internet of things

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Robust and Scalable Power System State Estimation via Composite Optimization

arXiv

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arXiv 2017年

作者： Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center and the Electrical and Computer Engineering Department University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Tongji University Shanghai200072 China

—In today’s cyber-enabled smart grids, high penetration of uncertain renewables, purposeful manipulation of meter readings, and the need for wide-area situational awareness, call for fast, accurate, and robust power system state estimation. The least-absolute-value (LAV) estimator is known for its robustness relative to the weighted least-squares (WLS) one. However, due to nonconvexity and nonsmoothness, existing LAV solvers based on linear programming are typically slow, hence inadequate for real-time system monitoring. This paper develops two novel algorithms for efficient LAV estimation, which draw from recent advances in composite optimization. The first is a deterministic linear proximal scheme that handles a sequence of (5 ∼ 10 in general) convex quadratic problems, each efficiently solvable either via off-the-shelf toolboxes or through the alternating direction method of multipliers. Leveraging the sparse connectivity inherent to power networks, the second scheme is stochastic, and updates only a few entries of the complex voltage state vector per iteration. In particular, when voltage magnitude and (re)active power flow measurements are used only, this number reduces to one or two, regardless of the number of buses in the network. This computational complexity evidently scales well to large-size power systems. Furthermore, by carefully mini-batching the voltage and power flow measurements, accelerated implementation of the stochastic iterations becomes possible. The developed algorithms are numerically evaluated using a variety of benchmark power networks. Simulated tests corroborate that improved robustness can be attained at comparable or markedly reduced computation times for medium- or large-size networks relative to existing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Electric power transmission networks

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A data-driven gradient algorithm for high-precision quantum control

arXiv

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arXiv 2017年

作者： Wu, Re-Bing Chu, Bing Owens, David H. Rabitz, Herschel Department of Automation Tsinghua University Beijing100084 China Center for Quantum Information Science and Technology BNRist Beijing100084 China School of Electronic and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Department of Automation Zhengzhou University Zhengzhou450001 China Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom Department of Chemistry Princeton University PrincetonNJ08544 United States

In the quest to achieve scalable quantum information processing technologies, gradient-based optimal control algorithms (e.g., GRAPE) are broadly used for implementing high-precision quantum gates, but their performance is often hindered by deterministic or random errors in the system model and the control electronics. In this paper, we show that GRAPE can be taught to be more effective by jointly learning from the design model and the experimental data obtained from process tomography. The resulting data-driven gradient optimization algorithm (d-GRAPE) can in principle correct all deterministic gate errors, with a mild efficiency loss. The d-GRAPE algorithm may become more powerful with broadband controls that involve a large number of control parameters, while other algorithms usually slow down due to the increased size of the search space. These advantages are demonstrated by simulating the implementation of a two-qubit CNOT gate. Copyright © 2017, The Authors. All rights reserved.

关键词： Random errors

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Complete stability of delayed recurrent neural networks with Gaussian activation functions

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Neural networks : the official journal of the International Neural Network Society 2017年 85卷 21-32页

作者： Peng Liu Zhigang Zeng Jun Wang School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: liupengjz@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: zgzeng@***. Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong. Electronic address: jwang.cs@cityu.edu.hk.

This paper addresses the complete stability of delayed recurrent neural networks with Gaussian activation functions. By means of the geometrical properties of Gaussian function and algebraic properties of nonsingular M-matrix, some sufficient conditions are obtained to ensure that for an n-neuron neural network, there are exactly 3 equilibrium points with 0≤k≤n, among which 2 and 3-2 equilibrium points are locally exponentially stable and unstable, respectively. Moreover, it concludes that all the states converge to one of the equilibrium points; i.e., the neural networks are completely stable. The derived conditions herein can be easily tested. Finally, a numerical example is given to illustrate the theoretical results.

关键词： Complete stability Gaussian functions Recurrent neural networks Time-varying delays

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Data-based Networked Tracking control System with Time Delay in the Forward Channel 35

Data-based Networked Tracking Control System with Time Delay...

引用

第35届中国控制会议

作者： TONG Shiwen QIAN Dianwei WANG Song JIANG Shan TIAN Kuo FANG Jianjun DENG Xianrui College of Automation Beijing Union University School of Computer and Control Engineering North China Electric Power University Beijing Key Laboratory of Information Service Engineering China United Engineering Corporation Beijing BBEF Science & Technology Co. Ltd. Department of Computer Science Tangshan Normal University

ISBN: (纸本)9781509009107

Networked Tracking control(NTC) is a challenging problem,especially for the unknown model system that only input-output data are expected to be *** paper has proposed a Data-based Networked Tracking control(DNTC)*** method uses fuzzy cluster modeling technology to establish the predictive model of the process according to the input-output *** the differences between the desired outputs and the predicted outputs of the process are treated as inputs of a Fuzzy Sliding Mode controller(FSMC) to obtain a string of future control *** control actions are packed and transferred from the controller side to the plant ***,the time delays in the forward communication channel are compensated by selecting appropriate control action in the plant *** outputs show rapid response and good accuracy of the proposed method.

关键词： Networked tracking control fuzzy cluster modeling fuzzy sliding mode control time delay

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Transfer learning for diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging data

arXiv

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arXiv 2017年

作者： Zheng, Qiang Tasian, Gregory Fan, Yong Department of Radiology School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States School of Computer and Control Engineering Yantai University Yantai264005 National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China Children's Hospital of Philadelphia PhiladelphiaPA19104 United States

Classification of ultrasound (US) kidney images for diagnosis of congenital abnormalities of the kidney and urinary tract (CAKUT) in children is a challenging task. It is desirable to improve existing pattern classification models that are built upon conventional image features. In this study, we propose a transfer learning-based method to extract imaging features from US kidney images in order to improve the CAKUT diagnosis in children. Particularly, a pre-trained deep learning model (imagenet-caffe-alex) is adopted for transfer learning-based feature extraction from 3-channel feature maps computed from US images, including original images, gradient features, and distanced transform features. Support vector machine classifiers are then built upon different sets of features, including the transfer learning features, conventional imaging features, and their combination. Experimental results have demonstrated that the combination of transfer learning features and conventional imaging features yielded the best classification performance for distinguishing CAKUT patients from normal controls based on their US kidney images. Copyright © 2017, The Authors. All rights reserved.

关键词： Ultrasonic imaging

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Fostering cooperation of selfish agents through public goods in relation to the loners

引用

Physical Review E 2016年第3期93卷 032320-032320页

作者： Jianlei Zhang Zengqiang Chen Zhongxin Liu Department of Automation College of Computer and Control Engineering Nankai University Tianjin 300071 People's Republic of China and Tianjin Key Laboratory of Intelligent Robotics Computer and Control Engineering Nankai University Tianjin 300071 People's Republic of China

Altruistic behaviors in multiplayer groups have obtained great attention in the context of the public goods game, which poses a riddle from the evolutionary viewpoint. Here we focus on a particular type of public goods game model in which the benefits of cooperation are either discounted or synergistically enhanced at the appearance of multiple cooperators in a group. Moreover, we focus on the three-strategies profile by adding the role of loners, besides the often-used cooperation and defection. Using the replicator dynamic equations, we investigate a range of dynamical portraits that characterizes the properties of the steady state. Analysis results indicate that loners and cooperators both have chances to be the stable equilibrium points in the presence of perturbations, while defectors fail to do so in this three-strategy competition. Moreover, the coexistence state, in which all three strategies exist in equilibrium, can be led by suitable parameters and stabilized for perturbations. These results elucidate the interplay between the characteristics of the public goods game and evolutionary dynamics in well-mixed systems.

关键词： Social system dynamics Social networks Game theory models

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Steps toward Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2016年第4期3卷 345-348页

作者： Fei-Yue Wang Xiao Wang Lingxi Li Li Li IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) Research Center of Computational Experiments and Parallel Systems the National University of Defense Technology Qingdao Academy of Intelligent Industries (QAII) QingdaoShandongChinaand SKL-MCCSCASIA Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis Department of Automation Tsinghua University Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies

The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the ''new normal'' of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS. © 2014 Chinese Association of automation.

关键词： control systems Electrical engineering

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