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Evolution and maintenance of cooperation via inheritance of neighborhood relationship

Chinese Science Bulletin 2013年第28期58卷 3491-3498页

作者： TAN ShaoLin Lü JinHu YU XingHuo HILL David John The Key Laboratory of System and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences School of Electrical and Computer Engineering RMIT University Department of Electrical and Electronic Engineering The University of Hong Kong School of Electrical and Information Engineering University of Sydney

Cooperative behaviors are ubiquitous in nature and human *** is very important to understand the internal mechanism of emergence and maintenance of *** we know now,the offsprings inherit not only the phenotype but also the neighborhood relationship of their *** recent research results show that the interactions among individuals facilitate survival of cooperation through network reciprocity of clustering *** paper aims at introducing an inheritance mechanism of neighborhood relationship to explore the evolution of *** detail,a mathematical model is proposed to characterize the evolutionary process with the above inheritance *** analysis and numerical simulations indicate that high-level cooperation can emerge and be maintained for a wide variety of cost-to-benefit ratios,even if mutation happens during the evolving process.

关键词：合作机制邻里关系维护演变进化过程人类社会遗传机制数学模型

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Covariance free incremental principal component analysis with exact mean update

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Journal of Computational Information systems 2013年第16期9卷 6703-6710页

作者： Zeng, Xueqiang Li, Guozheng The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Computer Center Nanchang University Nanchang 330029 China Department of Control Science and Engineering Tongji University Shanghai 201804 China

Incremental feature extraction is an essential data preprocessing technique for large-scale and streaming data mining. Among various covariance matrix-free Incremental Principal Component Analysis (IPCA) methods, Candid Covariance-free Incremental Principal Component Analysis (CCIPCA) is a state-of-the art algorithm. Since the training samples are required to be centred, CCIPCA applies an approximate centric alignment on the input data, where only the current sample is correctly centred and all historical data are not updated properly. In this paper, we propose a novel centred incremental principal component analysis algorithm with exact historical mean update, where not only the current sample is centred, but also all historical data are updated by the current mean correctly. Compared to CCIPCA, the proposed method converges more quickly, and the performance improvement is especially obvious when the data's inherent covariance is not stable. The experiments on real streaming dataset show that the proposed method is much superior to CCIPCA in convergence speed. © 2013 Binary Information Press.

关键词： Principal component analysis

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Erratum to “Consensus seeking over directed networks with limited information communication” [Automatica 49 (2) (2013) 610–618]

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Automatica 2014年第9期50卷 2430-2431页

作者： Dequan Li Qipeng Liu Xiaofan Wang Zongli Lin School of Science Anhui University of Science and Technology Huainan 232001 Anhui Province PR China Department of Automation Shanghai Jiao Tong University Shanghai 200240 PR China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 PR China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 USA

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Min-max MPC for LPV systems subject to Actuator Saturation by a Saturation-dependent Lyapunov Function

Min-max MPC for LPV Systems subject to Actuator Saturation b...

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第三十二届中国控制会议

作者： ZHANG Langwen WANG Jingcheng LI Kang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast

ISBN: (纸本)9781479900305

In this paper,we present a model predictive control algorithm for input-saturated systems by a saturation-dependent Lyapunov function *** saturation-dependent Lyapunov function captures the real-time information on the severity of saturation and thus leads to less conservative results in controller design.A set invariance condition for the systems with input saturation is presented.A min-max MPC algorithm is proposed for the linear parameter-varying(LPV) systems based on the invariant *** MPC controller is determined by solving a linear matrix inequality(LMI) optimization *** example demonstrates the effectiveness of the proposed algorithm.

关键词： Model Predictive control Linear parameter-varying Actuator saturation Saturation-dependent

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Robust H∞ control with partly quantized information

Robust H∞ control with partly quantized information

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第三十二届中国控制会议

作者： GE Yang WANG Jingcheng LI Kang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Electronics Electrical Engineering and Computer ScienceQueen's University Belfast

ISBN: (纸本)9781479900305

This paper is concerned with the stability and stabilizability problems of networked control systems（NCSs） with partly quantized *** precisely,the remote state variables transported from other sub-systems experience quantization errors,while the local state variables do *** consideration is much more natural in NCSs due to the distributive nature of *** errors are represented as convex poly-topic *** on the Lyapunov-Krasovskii （L-K） functional approach,sufficient conditions for the existence of a quantized robust Hstate feedback controller for NCSs are *** conditions are obtained in terms of bilinear matrix inequalities（BMIs）.Furthermore,a cone complementarity algorithm is utilized to convert these BMIs into a convex optimization ***,a simulation example is provided to demonstrate the efficiency of proposed theorems.

关键词： robust control quantized feedback control partly quantized information

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User Identification Based on Multiple Attribute Decision Making in Social Networks

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China Communications 2013年第12期10卷 37-49页

作者：叶娜张银亮董丽丽边根庆 Enjie LIU Gordon J.Clapworthy School of Electronic and Information Engineering Xi'an Jiaotong University School of Information and Control Engineering Xi'an University of Architecture and Technology Department of Computer Science and Technology University of Bedfordshire

Social networks are becoming increasingly popular and influential,and users are frequently registered on multiple networks simultaneously,in many cases leaving large quantities of personal information on each *** is also a trend towards the personalization of web applications;to do this,the applications need to acquire information about the particular *** maximise the use of the various sets of user information distributed on the web,this paper proposes a method to support the reuse and sharing of user profiles by different applications,and is based on user profile *** realize this goal,the initial task is user identification,and this forms the focus of the current paper.A new user identification method based on Multiple Attribute Decision Making(MADM) is described in which a subjective weight-directed objective weighting,which is obtained from the Similarity Weight method,is proposed to determine the relative weights of the common *** Synthetic Evaluation is used to determine the equivalence of *** results show that the method is both feasible and effective despite the incompleteness of the candidate user dataset.

关键词： weighted algorithm fuzzy match-ing cooperative communication network con-vergence heterogeneous networks

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Parallelized Jaccard-Based Learning Method and MapReduce Implementation for Mobile Devices Recognition from Massive Network Data

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China Communications 2013年第7期10卷 71-84页

作者：刘军李银周 Felix Cuadrado Steve Uhlig 雷振明 Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Department of Electronic Engineering and Computer Science Queen MaryUniversity of London

The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user *** this paper,we propose a novel method for mobile device model recognition by using statistical information derived from large amounts of mobile network traffic ***,we create a Jaccardbased coefficient measure method to identify a proper keyword representing each mobile device model from massive unstructured textual HTTP access *** handle the large amount of traffic data generated from large mobile networks,this method is designed as a set of parallel algorithms,and is implemented through the MapReduce framework which is a distributed parallel programming model with proven low-cost and high-efficiency *** using real data sets show that our method can accurately recognise mobile client models while meeting the scalability and producer-independency requirements of large mobile network *** show that a 91.5% accuracy rate is achieved for recognising mobile client models from 2 billion records,which is dramatically higher than existing solutions.

关键词： mobile device recognition data mining Jaccard coefficient measurement distributed computing MapReduce

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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INTENSIVE CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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Design and Implementation of Stereo Vision systems Based on FPGA for 3D Information

Design and Implementation of Stereo Vision Systems Based on ...

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16th FIRA RoboWorld Congress, FIRA 2013

作者： Tu, Kuo-Yang Chiu, Chen-Yu Li, Shih-An Baltes, Jacky Institute of System Information and Control National Kaohsiung First University of Science and Technology 2 Jouyue Road Nantsu 811 Kaohsiung City Taiwan Department of Electrical Engineering Tamkang University Taiwan Department of Computer Science University of Manitoba Canada

ISBN: (纸本)9783642404085

The purpose of this paper is to utilize Field Programmable Gate Array (FPGA) to perform stereo vision distance detection. However, the stereo vision built by two cameras makes memory space lacking and image process slow under the constraints of FPGA application. In this paper, efficient memory space allocation and hardware calculation for stereo vision detection built in a system on a Programmable Chip (SOPC) based on FPGA are proposed. The hardware for stereo vision distance calculation includes the processing for the images of gray, binary, dilation, erosion, etc, and image geometry method for the vision distance through information of phase differences between two lenses. In addition, the simple hardware algorithm of background image subtraction to capture an object image from a series of image frames is also included. The totally hardware to perform stereo vision distance detection is difficult implementation, but firmware (some calculation in software) is flexible and quick to develop. Therefore, the performance of stereo vision distance detection according to hardware and firmware is compared. Finally, the distance calculation between objects and the lenses is demonstrated by practical experiments. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Stereo vision

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On the Convergence Rate of a Jacobi Algorithm for Cooperative Distributed MPC

On the Convergence Rate of a Jacobi Algorithm for Cooperativ...

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IEEE Annual Conference on Decision and control

作者： Dominic Gross Olaf Stursberg Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel (Germany)

ISBN: (纸本)9781467357159

This paper investigates the convergence of an iterative distributed model predictive control (DMPC) scheme for linear systems interconnected by dynamics and costs. The DMPC scheme is based on a Jacobi-type iteration and exchange of primal variables. Previous results show that, in the limit, the scheme converges to the Pareto optimal solution but no results on the convergence rate are given. We will first establish a bound on the convergence rate and show that weights used in the scheme and strength of coupling between subsystems have a strong influence on this bound. Subsequently, two approaches to determine the weights are compared. Random numerical examples are used to compare the theoretical bound on the convergence rate with the actual convergence of the scheme.

关键词： Convergence Couplings Vectors Jacobian matrices Cost function Predictive control

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