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arXiv 2017年

作者： Orabona, Francesco Tommasi, Tatiana Department of Computer Science Stony Brook University NY United States Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Italy

Deep learning methods achieve state-of-the-art performance in many application scenarios. Yet, these methods require a significant amount of hyperparameters tuning in order to achieve the best results. In particular, tuning the learning rates in the stochastic optimization process is still one of the main bottlenecks. In this paper, we propose a new stochastic gradient descent procedure for deep networks that does not require any learning rate setting. Contrary to previous methods, we do not adapt the learning rates nor we make use of the assumed curvature of the objective function. Instead, we reduce the optimization process to a game of betting on a coin and propose a learning-rate-free optimal algorithm for this scenario. Theoretical convergence is proven for convex and quasi-convex functions and empirical evidence shows the advantage of our algorithm over popular stochastic gradient algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： Learning algorithms

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Model reduction for linear parameter varying systems using scaled diagonal dominance

Model reduction for linear parameter varying systems using s...

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American control Conference

作者： Harald Pfifer Tamas Peni Aerospace and Engineering Mechanics Department University of Minnesota USA Systems and Control Laboratory of Institute for Computer Science and Control (MTA-SZTAKI) Budapest Hungary

ISBN: (纸本)9781467386838

A model-reduction method for linear, parameter-varying (LPV) systems based on parameter-varying balanced realizations is proposed. In general, this requires the solution of a large set of linear matrix inequalities, leading to numerical issues and high computational cost. It has been recognized recently that semidefinite optimization problems (SDP) can be cast into second order cone programs (SOCP) by replacing the positive definiteness constraints with stronger, scaled diagonal dominance conditions. Since the scalability of SOCP solvers is much better than that of the SDPs, the new formulation allows solving large scale model reduction problems more efficiently. A numerical example is provided to demonstrate the efficiency of the approach.

关键词： Reduced order systems Symmetric matrices Mathematical model Linear systems Linear matrix inequalities controllability Observability

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Finding the Number of Clusters in a Dataset Using an Information Theoretic Hierarchical Algorithm

Finding the Number of Clusters in a Dataset Using an Informa...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： M. Aghagolzadeh H. Soltanian-Zadeh B. N. Araabi A. Aghagolzadeh Department of Electrical and Computer Engineering Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

One of the most challenging problems of clustering is detecting the exact number of clusters in a dataset. Most of the previous methods, presented to solve this problem, estimate the number of clusters with model based algorithms, which are not able to detect all types of clusters and also face a problem in detecting coupled clusters in a dataset. In this paper we propose a new method for finding the number of clusters in a dataset utilizing information theory and a top-down hierarchical clustering algorithm. The algorithm starts from a large number of clusters and reduces one cluster in any iteration and then allocates its data points to the remaining clusters. Finally, by measuring information potential, the exact number of clusters in a desired dataset is detected. Our method shows high capability and stability in detecting the number of clusters even in complex datasets, as it is computational efficient too. We show the effectiveness of the proposed method by experimenting on several artificial and real datasets and comparing its results with two developed methods for finding the number of clusters in a dataset. The comparisons show superiority of the proposed method.

关键词： Clustering algorithms Entropy Face detection Process control Intelligent control Information theory Stability Computational efficiency Electric variables measurement Computational complexity

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CPRL - An Extension of Compressive Sensing to the Phase Retrieval Problem 12

CPRL - An Extension of Compressive Sensing to the Phase Retr...

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Annual Conference on Neural Information Processing Systems

作者： Henrik Ohlsson Allen Y. Yang Roy Dong S. Shankar Sastry Division of Automatic Control Department of Electrical Engineering Linkoping University Sweden Department of Electrical Engineering and Computer Sciences University of California at Berkeley CA USA Department of Electrical Engineering and Computer Sciences University of California at Berkeley CA USA

ISBN: (纸本)9781627480031

While compressive sensing (CS) has been one of the most vibrant research fields in the past few years, most development only applies to linear models. This limits its application in many areas where CS could make a difference. This paper presents a novel extension of CS to the phase retrieval problem, where intensity measurements of a linear system are used to recover a complex sparse signal. We propose a novel solution using a lifting technique - CPRL, which relaxes the NP-hard problem to a nonsmooth semidefinite program. Our analysis shows that CPRL inherits many desirable properties from CS, such as guarantees for exact recovery. We further provide scalable numerical solvers to accelerate its implementation.

关键词： Compressed sensing CONTAINMENT SPRAY carbon monosulfide Cesium Nondeterministic polynomial-time hard conditioned stimulus retrieval Linear system program area

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A Practical Cross-Device Federated Learning Framework over 5G Networks

arXiv

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arXiv 2022年

作者： Yang, Wenti Wang, Naiyu Guan, Zhitao Wu, Longfei Du, Xiaojiang Guizani, Mohsen School of Control and Computer Engineering North China Electric Power University China Department of Mathematics & Computer Science Fayetteville State University United States Department of Electrical and Computer Engineering Stevens Institute of Technology HobokenNJ United States Department of Computer Science and Engineering Qatar University Qatar

The concept of federated learning (FL) was first proposed by Google in 2016. Thereafter, FL has been widely studied for the feasibility of application in various fields due to its potential to make full use of data without compromising the privacy. However, limited by the capacity of wireless data transmission, the employment of federated learning on mobile devices has been making slow progress in practical. The development and commercialization of the 5th generation (5G) mobile networks has shed some light on this. In this paper, we analyze the challenges of existing federated learning schemes for mobile devices and propose a novel cross-device federated learning framework, which utilizes the anonymous communication technology and ring signature to protect the privacy of participants while reducing the computation overhead of mobile devices participating in FL. In addition, our scheme implements a contribution-based incentive mechanism to encourage mobile users to participate in FL. We also give a case study of autonomous driving. Finally, we present the performance evaluation of the proposed scheme and discuss some open issues in federated learning. Copyright © 2022, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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Fuzzy Model of the IT Project Environment Impact on its Completion

Fuzzy Model of the IT Project Environment Impact on its Comp...

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International Conference on Advanced computer Information Technologies (ACIT)

作者： Nadiia Vasylkiv Iryna Turchenko Lesia Dubchak Department of Information Computer Systems and Control Ternopil National Economic University Ternopil Ukraine Department of Computer Engineering Ternopil National Economic University Ternopil Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

A fuzzy model for estimating the impact of the IT project environment on its implementation is developed, the inputs of which are environmental factors, financial, human resources and the output is the completion of the project, which allows timely response to uncertain and risky situations for the project. The proposed fuzzy model can be used to effectively manage projects of various directions and make changes to their implementation in order to complete project work in a timely and successful manner.

关键词： Mathematical model Fuzzy logic Input variables Environmental factors Project management Computational modeling Matlab

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Adaptive controller Design for Anti-Slip System of EV

Adaptive Controller Design for Anti-Slip System of EV

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Phornsuk Ratiroch-Anant Hiroshi Hirata Masatoshi Anabuki Shigeto Ouchi Department of Control Engineering Faculty of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Applied Computer Engineering Tokai University Hiratsuka Japan

The design strategy of adaptive controller for anti-slip system of EV (electric vehicle) is proposed. The proposed system is constructed by preparing both systems of disturbance observer and parameter estimation. The load variation of the tire slip is observed as the equivalent disturbance of motor system by employing the adaptive disturbance observer, and the vehicle speed is estimated. The tire slip is appropriately controlled by means of the feedback of the speed deviation between wheel speed and estimated vehicle speed. It is proved by the numerical simulations that the proposed methods provide satisfactory performance. Furthermore, the practical DC motor experiment set, which can give various slips, is constructed in order to investigate the effect of proposed anti-slip control system. It is verified that the proposed strategy is useful as one approach of anti-slip control

关键词： Programmable control Adaptive control control systems Tires DC motors Electric vehicles Parameter estimation Load management Feedback Wheels

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On the control of the Collector Field Outlet Temperature of Shiraz 250 KW Solar Power Plant

On the Control of the Collector Field Outlet Temperature of ...

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2012 Asian Pacific Conference on Energy,Environment and Sustainable Development(APEESD 2012)

作者： Mostafa Zamani Mohi Abadi Seyed Mohammad Hessam Mohammadi Seyed Ali Akbar Safavi Seyed Vahid Naghavi School of E. Learning instrumentation and automation Shiraz University School of Electrical and Computer Engineering Shiraz University Control Electrical and Computer Engineering Department Shiraz University

This paper presents a control study of the real Shiraz 250 KW solar power plant together with a modeling and a monitoring interface. Here, a PID controller is developed to control the outlet oil temperature of the collector field of the solar power plant as a standard tool for industrial automation. First the power plant is modeled within MATLAB environment and the model is verified with the real data of the power plant. Then an HMI environment is developed within the Lab VIEWsoftwarewhile incorporating the model developed in MATLAB. The simulation results showed that a fixed-coefficient PID failed to provide the desired results over a year and the best coefficients for each month were calculated. The friendly and accurate developed environment within MATLAB and Lab VIEW provide a valuable tool for modeling and control studies and monitoring of the real power plant.

关键词： Collector Field Outlet Temperature control Solar Power Plant MATLAB LabVIEW

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Automatic Identification of Functionally Untestable Cell-Aware Faults in Microprocessors

Automatic Identification of Functionally Untestable Cell-Awa...

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Asian Test Symposium (ATS)

作者： Nikolaos I. Deligiannis Tobias Faller Iacopo Guglielminetti Riccardo Cantoro Bernd Becker Matteo Sonza Reorda Department of Control and Computer Engineering (DAUIN) Politecnico di Torino Turin Italy Department of Computer Science University of Freiburg Freiburg Germany STMicroelectronics Turin Italy

In-field test of microprocessors is a major topic for the industry, especially in the safety-critical domain, where the respective standards mandate high test coverage thresholds. The dominant fault models used are the transition delay and the stuck-at fault model. However, the adoption of very advanced semiconductor technologies to manufacture devices used in safety-critical applications pushes toward considering new fault models that are better suited to catch subtle and age-related defects. Among the other phenomena, latent cell-internal defects emerged as relevant causes for several failures. Hence, the necessity for the Cell-Aware Test (CAT) was born, and the inclusion of the CAT fault model in the latest safety standards. Although CAT amends the issue of the numerous test escapes, it may suffer as well from the presence of functionally untestable faults that may pollute the overall test efficiency with their presence. In this paper, we propose a solution, based on formal methods, for the automatic identification of functionally untestable faults under the Cell-Aware fault model for the case where the DUT is a fully pipelined processor. As a case study, we used the RISC-V processor RI5CY for which we applied the minimum constraints required to ensure a functional behavior to demonstrate the effectiveness and impact of the approach. With the considered constraints, a significant percentage of functionally untestable faults was located in the several modules within the processor. Furthermore, the method allows to flexibly take into account any constraint stemming from the system configuration and the application. The obtained results have been validated by resorting to commercial EDA tools.

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Insulating materials for realising carbon neutrality:Opportunities,remaining issues and challenges

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High Voltage 2022年第4期7卷 610-632页

作者： Chuanyang Li Yang Yang Guoqiang Xu Yao Zhou Mengshuo Jia Shaolong Zhong Yu Gao Chanyeop Park Qiang Liu Yalin Wang Shakeel Akram Xiaoliang Zeng Yi Li Fangwei Liang Bin Cui Junpeng Fang Lingling Tang Yulin Zeng Xingtao Hu Jiachen Gao Giovanni Mazzanti Jinliang He Jianxiao Wang Davide Fabiani Gilbert Teyssedre Yang Cao Feipeng Wang Yunlong Zi The State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Simpson Querrey Institute Northwestern UniversityEvanstonIllinoisUSA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA Department of Information Technology and Electrical Engineering ETH ZürichZürichSwitzerland School of Electrical and Information Engineering Tianjin UniversityTianjinChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina College of Electrical Engineering Sichuan UniversityChengduChina Shenzhen Institute of Advanced Technology Chinese Academy of Sciences ShenzhenShenzhenChina School of Electrical Engineering Wuhan UniversityWuhanChina School of Integrated Circuits Tsinghua UniversityBeijingChina Jiangsu Jinxin Electric Appliance Co.Ltd. YangzhouChina Tai'an Tiancheng Safety Evaluation Co. Ltd.Tai'anChina Department Electrical Electronic and Information EngineeringUniversity of BolognaBolognaItaly National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijingChina Laplace Paul Sabatier Universityand CNRSToulouseFrance Electrical and Computer Engineering University of ConnecticutStorrsConnecticutUSA State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqingChina Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)GuangzhouChina De

The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment *** material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and *** goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first *** engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are *** materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being *** the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material *** is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality *** authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.

关键词： neutral insulation extreme

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