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JOURNAL OF NONLINEAR FUNCTIONAL ANALYSIS 2018年 2018卷

作者： Su, Hongyan Zhao, Jing Qingdao Univ Sci & Technol Dept Math Qingdao 266000 Peoples R China Civil Aviat Univ China Coll Sci Tianjin 300300 Peoples R China

In this paper, we introduce parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of demicontractive operators. We propose a way of selecting the stepsizes such that the implementation of our algorithms does not need any prior information about operator norms. It thus avoids the difficult task of estimating the operator norms. We also combine the process of cyclic and parallel together and propose two mixed iterative algorithms without prior knowledge of operator norms. The weak convergence theorems of the proposed algorithms are established under some suitable control conditions in a real Hilbert space. Some numerical experiments are given for the proposed iterative algorithms.

关键词： Multiple-set split equality common fixed-point problem Demicontractive operator Weak convergence iterative algorithm Hilbert space

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An adaptive switching scheme for iterative computing in the cloud

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Frontiers of Computer Science 2014年第6期8卷 872-884页

作者： Yu ZHANG Xiaofei LIAO Hai JIN Li LIN Feng LU Service Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

Delta-based accumulative iterative computation （DAIC） model is currently proposed to support iterative algorithms in a synchronous or an asynchronous way. However, both the synchronous DAIC model and the asynchronous DAIC model only satisfy some given conditions, respectively, and perform poorly under other conditions either for high synchronization cost or for many redundant activations. As a result, the whole performance of both DAIC models suffers from the serious network jitter and load jitter caused by multi- tenancy in the cloud. In this paper, we develop a system, namely Hyblter, to guarantee the performance of iterative algorithms under different conditions. Through an adaptive execution model selection scheme, it can efficiently switch between synchronous and asynchronous DAIC model in order to be adapted to different conditions, always getting the best performance in the cloud. Experimental results show that our approach can improve the performance of current solutions up to 39.0%.

关键词： iterative algorithm computational skew communication skew cloud delta-based accumulative iterative computation

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Measures of genuine multipartite entanglement for graph states

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Chinese Physics B 2014年第5期23卷 96-101页

作者：郭群群陈小余王赟赟 College of Information and Electronic Engineering Zhejiang Gongshang University

Graph states are special multipartite entangled states that have been proven useful in a variety of quantum information tasks. We address the issue of characterizing and quantifying the genuine multipartite entanglement of graph states up to eight qubits. The entanglement measures used are the geometric measure, the relative entropy of entanglement, and the logarithmic robustness, have been proved to be equal for the genuine entanglement of a graph state. We provide upper and lower bounds as well as an iterative algorithm to determine the genuine multipartite entanglement.

关键词： genuine entanglement graph state iterative algorithm

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An Alternating Minimization algorithm for Binary Image Restoration

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2012年第2期21卷 883-888页

作者： Zhang, Jianjun Shanghai Univ Dept Math Shanghai 200444 Peoples R China

The problem we will consider in this paper is binary image restoration. It is, in essence, difficult to solve because of the combinatorial nature of the problem. To overcome this difficulty, we propose a new minimization model by making use of a new variable to enforce the image to be binary. Based on the proposed minimization model, we present a fast alternating minimization algorithm for binary image restoration. We prove the convergence of the proposed alternating minimization algorithm. Experimental results show that the proposed method is feasible and effective for binary image restoration.

关键词： Blur fast Fourier transform (FFT) Gaussian noise image restoration iterative algorithm regularization

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Complex Variable Multi-phase Distribution System State Estimation Using Vectorized Code

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Journal of Modern Power Systems and Clean Energy 2020年第4期8卷 679-688页

作者： Izudin Džafić Rabih A.Jabr Tarik Hrnjić IEEE Faculty of Electrical Engineering University of SarajevoZmaja od Bosne bb 71000 SarajevoBosnia and Herzegovina Department of Electrical&Computer Engineering American University of BeirutP.O.Box 11-0236Riad El-Solh/Beirut 11072020Lebanon

With the advent of advanced energy management systems in distribution systems,there is a growing interest in rapid and reliable code for distribution system state estimation(DSSE)in large-scale *** DSSE methods employed in the industry are based on load scaling as they are well suited to the abundance of *** to the paucity of real-time measurements in DSSE,phasor measurement units(PMUs)have been proposed as a potential solution to increase the estimation ***,load scaling methodologies are not extendable for exploiting *** paper proposes a high-performance DSSE method that can handle the PMUs together with all common measurement types in industrial *** using Wirtinger calculus,the method operates entirely in complex variables and employs the latest version of advanced vector extensions(AVX-2)to reap the maximum potential of computer processing *** paper highlights the derivation of complex DSSE in matrix form,from which one can infer the implications on code reliability and *** results are reported on large-scale multi-phase distribution systems,and they are contrasted with a publicly available code for DSSE in real *** simulation results show that loop unrolling in AVX-2 contributes about a two-fold increase in the solving speed.

关键词： iterative algorithm least squares approximation optimization method distribution system state estimation

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A fast PID type parameter optimal iterative learning control algorithm for non-positive plants

A fast PID type parameter optimal iterative learning control...

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Chinese Control Conference (CCC)

作者： Hengjie Li Xiaohong Hao School of Electrical and Information Engineering Lanzhou University of Technology Gansu 730050 China

In order to obtain faster and more accuracy transient tracking performances for non-positive plants, a fast proportional integral difference (PID) type parameter optimal iterative learning control algorithm is proposed. In the algorithm, the PID type operators are introduced to enhance convergence speed and a suitable set of basis functions is added to avoid the algorithm plunge into local optimal when the plant is not positive. Theoretic proof shows that the algorithm monotone convergence to zero no matter the system plant is positive or not. Finally, simulations show that the algorithm also has a faster convergence speed compare with other similar algorithms.

关键词： Convergence algorithm design and analysis iterative algorithm Equations Eigenvalues and eigenfunctions Time domain analysis Mathematical model

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A Fast Parameter Optimal iterative Learning Control algorithm

A Fast Parameter Optimal Iterative Learning Control Algorith...

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International Conference on Embedded Software and Systems Symposia, ICESS Symposia

作者： Hengjie Li Xiaohong Hao Weitao Xu School of Electrical and Information Engineering Lanzhou University of Technology Lanzhou Gansu China

In order to obtain faster and more accuracy transient tracking performances in iterative domain, a high-order proportional integral difference type parameter optimal iterative learning control algorithm based on norm performance index is proposed. In the algorithm, the proportional integral difference type operator is introduced to expend the dimension of the algorithm and to increase the free-degree of the optimal parameter. Theoretic proof shows that the convergence of the algorithm is monotonic no matter the plant is positive or not, and the tracking error will converge monotonically to zero when the plant is positive. Finally, simulations show that the tracking error of the proposed algorithm converges monotonically and faster than other similar algorithms.

关键词： Convergence algorithm design and analysis Mathematical model iterative algorithm Equations Gallium nitride Approximation algorithms

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Toward High-Performance Delta-Based iterative Processing with a Group-Based Approach

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Journal of Computer Science & Technology 2022年第4期37卷 797-813页

作者： Hui Yu Xin-Yu Jiang Jin Zhao Hao Qi Yu Zhang Xiao-Fei Liao Hai-Kun Liu Fu-Bing Mao Hai Jin National Engineering Research Center for Big Data Technology and System Huazhong University of Science and TechnologyWuhan 430074China Service Computing Technology and System Laboratory Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Laboratory Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China

Many systems have been built to employ the delta-based iterative execution model to support iterative algorithms on distributed platforms by exploiting the sparse computational dependencies between data items of these iterative algorithms in a synchronous or asynchronous approach. However, for large-scale iterative algorithms, existing synchronous solutions suffer from slow convergence speed and load imbalance, because of the strict barrier between iterations;while existing asynchronous approaches induce excessive redundant communication and computation cost as a result of being barrier-free. In view of the performance trade-off between these two approaches, this paper designs an efficient execution manager, called Aiter-R, which can be integrated into existing delta-based iterative processing systems to efficiently support the execution of delta-based iterative algorithms, by using our proposed group-based iterative execution approach. It can efficiently and correctly explore the middle ground of the two extremes. A heuristic scheduling algorithm is further proposed to allow an iterative algorithm to adaptively choose its trade-off point so as to achieve the maximum efficiency. Experimental results show that Aiter-R strikes a good balance between the synchronous and asynchronous policies and outperforms state-of-the-art solutions. It reduces the execution time by up to 54.1% and 84.6% in comparison with existing asynchronous and the synchronous models, respectively.

关键词： iterative algorithm delta-based execution model efficiency

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Uplink radio resource allocation in orthogonal frequency-division multiple access heterogeneous networks with limited feedback

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IET COMMUNICATIONS 2014年第18期8卷 3451-3458页

作者： Dashti, Mina Mokari, Nader Abedi, Mohhamad Reza Islamic Azad Univ East Tehran Branch Dept Elect Engn Tehran *** Iran Tarbiat Modares Dept Elect & Comp Engn Tehran 14115349 Iran

Femtocell networks are expected to offer significant performance improvement with low cost. However, adaptive transmission based on maximising the sum rate of macro and femto networks requires perfect channel quality information (CQI) of the macro and femto links. This assumption requires an infinite resolution feedback link, which is not always practical since it requires an excessive amount of bandwidth. This study considers the problem of maximising average sum rate under the constraint of average maximum power transmission at macro and femto users. A suboptimal iterative algorithm is developed for finding the optimal CQI quantisers as well as the discrete power and rate at macro and femto transmitter for each quantised CQI level so as to maximise the average sum rate of the system. The author's numerical results give the number of bits required to sufficiently represent the CQI to achieve almost the maximum sum rate attained using full knowledge of the CQI.

关键词： resource allocation frequency division multiple access femtocellular radio iterative methods uplink radio resource allocation orthogonal frequency-division multiple access heterogeneous networks femtocell networks adaptive transmission macro networks femto networks channel quality information macro links femto links iterative algorithm CQI quantisers

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Multidimensional Reversible Solid Oxide Fuel Cell Modeling for Embedded Applications

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IEEE TRANSACTIONS ON ENERGY CONVERSION 2018年第2期33卷 692-701页

作者： Ma, Rui Gao, Fei Breaz, Elena Huangfu, Yigeng Briois, Pascal Univ Bourgogne Franche Comte FEMTO ST UMR CNRS 6174 Energy Dept F-90010 Belfort France FR CNRS 3539 Fuel Cell Lab F-90010 Belfort France Northwestern Polytech Univ Xian 710072 Shaanxi Peoples R China Tech Univ Cluj Napoca Cluj Napoca 400604 Romania Univ Bourgogne Franche Comte Dept MN2S FEMTO ST UMR CNRS 6174 F-25200 Montbeliard France

This paper presents a multiphysical modeling of a two-dimensional (2-D) reversible tubular solid oxide cell. The developed model can represent both a solid oxide electrolysis cell (SOEC) and solid oxide fuel cell (SOFC) operations. By taking into account of the electrochemical, fluidic, and thermal physical phenomena, the presented model can accurately describe the multiphysical effects inside a cell for both fuel cell and electrolysis cell operation under entire working range of cell current and temperature. In addition, an iterative solver is proposed which is used to solve the 2-D distribution of physical quantities along the tubular cell. The proposed model is suitable for embedded applications, such as real-time simulation or online diagnostic control. The reversible solid oxide cell model is then validated experimentally in both SOEC and SOFC configurations under different species partial pressures, operating temperatures, and current densities conditions.

关键词： Solid oxide electrolysis cell (SOEC) solid oxide fuel cell (SOFC) physical modeling multi-dimensional iterative algorithm

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