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International Conference on systems and Informatics (ICSAI)

作者： Chenggong Sun Xiwei Liu Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (数字)9798331510138

ISBN: (纸本)9798331510145

In this paper, we explore and establish several necessary and sufficient conditions that are instrumental in achieving consensus within second-order discrete-time multi-agent systems (SDMAS). Different with previous research, this study addresses the more intricate scenario where the velocity coupling matrix is distinct from the position coupling matrix. We introduce a novel eigenvector condition tailored to this challenge. Furthermore, in response to the burgeoning interest in multiweighted networks, this study is extended to SDMAS with multiple weights. We employ a technique, that rearranges the order of variables, to effectively simplify the analysis of multiweighted networks by transforming them into single-weighted equivalents. The efficacy of our method is substantiated through three numerical examples, which illustrate the practical value in elucidating consensus dynamics within SDMAS featuring diverse coupling matrices.

关键词： Couplings Sufficient conditions Instruments Numerical simulation Trajectory Numerical models Multiaccess communication Informatics Pragmatics Multi-agent systems

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Synchronization and control for multi-weighted and directed complex networks

arXiv

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arXiv 2021年

作者： Liu, Xiwei Department of Computer Science and Technology Tongji University China The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China

The study of complex networks with multi-weights has been a hot topic recently. For a network with a single weight, previous studies have shown that they can promote synchronization. But for complex networks with multi-weights, there are no rigorous analysis to show that synchronization can be reached faster. In this paper, the complex network is allowed to be directed, which will make the synchronization analysis difficult for multiple couplings. In virtue of the normalized left eigenvectors (NLEVec) corresponding to the zero eigenvalue of coupling matrices, we prove that if the Chebyshev distance between NLEVec is less than some value, which is defined as the allowable deviation bound, then the synchronization and control will be realized with sufficiently large coupling strengths, i.e., all coupling matrices do accelerate synchronization. Moreover, adaptive rules are also designed for the coupling strength. © 2021, CC BY.

关键词： Eigenvalues and eigenfunctions

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A Distributed Link Prediction Algorithm Based on Clustering in Dynamic Social Networks

A Distributed Link Prediction Algorithm Based on Clustering ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Han Yuan Yunlong Ma Feng Zhang Min Liu Weiming Shen Tongji University School of Electronic and Information Engineering Shanghai China Tongji University The Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781479986989

Link prediction in network attempts to predict the exist-yet-unknown links or future links in accordance with the node properties and the network typology. It has been used in many domains such as social network, biology experiment, and criminal investigations. Classical methods are based on graph topology structure and path features but few consider clustering information. Actually, clustering information plays an important role in link prediction, it connects the sparse nodes and other communities to form intensive communities. Besides the application of clustering, the MapReduce-based method is used to improve the efficiency. The validity of algorithm is verified by real-world datasets. The experimental results show that the proposed algorithm has a higher prediction accuracy and lower time complexity, and is more scalable than traditional methods executed by a single machine.

关键词： Prediction algorithms Clustering algorithms Indexes Prediction methods Algorithm design and analysis Heuristic algorithms Social network services

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Improvement of rotation matrix based differential limited feedback with DFT codebook and its application in CoMP environment

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Journal of Communications 2014年第6期9卷 498-505页

作者： Zhu, Yin Ji, Yusheng Wang, Ping Liu, Fuqiang Broadband Wireless Communications and Multimedia Laboratory Key Laboratory of Embedded System and Service Computing supported by Ministry of Education Tongji University Shanghai 201804 China National Institute of Informatics Tokyo Japan

Recently, exploiting the temporal correlation of slowly varied multiple input multiple output (MIMO) channels to further improve the system performance or the feedback efficient in MIMO wireless communication systems with limited feedback has been investigated in many papers. Among them, T. Kim et al. proposed a rotation matrix based differential feedback scheme which is shown to have good performance with regard to the system throughput for spatial multiplexing MIMO systems. Although the rotation matrix codebook and the precoding codebook in their scheme are optimally constructed, they are not fit for a practical system due to the structure constraints. In this paper, we propose to replace the optimal codebook in the rotation matrix based differential feedback scheme with discrete Fourier transform (DFT) structured codebook, and propose a search-based method to decrease the performance degradation induced by the un-optimality of the DFT codebook. In addition, the modified algorithm is also applied to a per-cell codebook based coordinated multi-point (CoMP) transmission system to verify its applicability to different MIMO scenarios. Simulation results show the effectiveness of our modified scheme. © 2014 Engineering and Technology Publishing.

关键词： Discrete Fourier transforms

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Hierarchical attention generative adversarial networks for cross-domain sentiment classification

arXiv

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arXiv 2019年

作者： Zhang, Yuebing Miao, Duoqian Wang, Jiaqi Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

Cross-domain sentiment classification (CDSC) is an importance task in domain adaptation and sentiment classification. Due to the domain discrepancy, a sentiment classifier trained on source domain data may not works well on target domain data. In recent years, many researchers have used deep neural network models for cross-domain sentiment classification task, many of which use Gradient Reversal Layer (GRL) to design an adversarial network structure to train a domain-shared sentiment classifier. Different from those methods, we proposed Hierarchical Attention Generative Adversarial Networks (HAGAN) which alternately trains a generator and a discriminator in order to produce a document representation which is sentimentdistinguishable but domain-indistinguishable. Besides, the HAGAN model applies Bidirectional Gated Recurrent Unit (Bi-GRU) to encode the contextual information of a word and a sentence into the document representation. In addition, the HAGAN model use hierarchical attention mechanism to optimize the document representation and automatically capture the pivots and non-pivots. The experiments on Amazon review dataset show the effectiveness of HAGAN. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A Stable and Distributed Community Detection Algorithm Based on Maximal Cliques

A Stable and Distributed Community Detection Algorithm Based...

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IEEE International Conference on systems, Man and Cybernetics

作者： Feng Gui Yunlong Ma Feng Zhang Min Liu Rong Yin Weiming Shen Tongji University School of Electronic and Information Engineering Shanghai China Tongji University The Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781479986989

In the research area of community detection which aims at detecting some highly cohesive vertex subsets in social network, there mainly exist some problems, such as the algorithms with comparatively excellent quality of the final partitioning usually have high time complexity and some other fast algorithms often result in low quality of partitioning or other disadvantages. Nowadays, the increasing demands for community detection in large-scale social networks necessitate the use of distributed and scalable methods to detect communities in an effective and efficient manner. Label propagation algorithm (LPA), whose time complexity is O (m) on a network with m edges, is a near linear time algorithm to detect community effectively. Besides, owing to having good scalability, the parallel version of LPA (DLPA) is suitable for community detection in large-scale social networks. However, DLPA synchronously updates the vertices labels, which usually brings about label oscillations and results in low quality of partitioning. In this paper, we analyze the drawbacks of DLPA and propose a novel method C-DLPA, which combines DLPA with the notion of maximal cliques and at the same time utilizes a new updating mechanism that updating each node' label by probability of its adjacent nodes, to make final partitioning become more accurate and to avoid oscillations effectively. The experimental results show that C-DLPA has better performance is not only low time cost by as much to avoid oscillations but its community detection accuracy compared with DLPA.

关键词： Oscillators Image edge detection Time complexity Partitioning algorithms Algorithm design and analysis Social network services Transforms

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Bridge the Gap Between Network-Based Inference Method and Global Ranking Method in Personal Recommendation

Bridge the Gap Between Network-Based Inference Method and Gl...

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IEEE Conference on Industrial Electronics and Applications

作者： Xiwei Liu Department of Computer Science and Technology Tongji University China The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai 200092 China

In this paper, we study the relationship between the network-based inference method and global ranking method in personal recommendation. By some theoretical analysis, we prove that the recommendation result under the... 详细信息

ISBN: (纸本)9781467386456

关键词： Eigenvalues and eigenfunctions Heating Bridges Inference algorithms Prediction algorithms Conferences Industrial electronics

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Clustering and Analysis of Household Power Load Based on HMM and Multi-factors

Clustering and Analysis of Household Power Load Based on HMM...

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International Conference on Computer Supported Cooperative Work in Design

作者： Hao Fang Yue Zhang Min Liu Weiming Shen School of Electronic and Information Engineering Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

With the advance of the information and communication technology, smart grid, and smart metering, residential electricity usage data are available for analyzing household usage pattern. However, most such usage pattern analyses have been based on smart meter data. Geographical location and environment factors have not been well considered. In order to have a better understanding of residential electricity usage pattern, this paper studies the usage pattern based on both environment data and smart meter data. A Hidden Markov Model (HMM) is applied to learn the consumption dynamic behavior under the corresponding environments and a clustering method is applied to discover the typical usage patterns. The environmental adaptation which indicates the household reaction to the environment during the electricity consumption is revealed.

关键词： Hidden Markov models Clustering algorithms Smart meters Meteorology Pattern analysis Analytical models Biological system modeling

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Genetic Fuzzy + PI Path Tracking Control of a Nonholonomic Mobile Robot*

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Chinese Journal of Electronics 2023年第1期20卷 31-34页

作者： Zhengcai Cao Yingtao Zhao Qidi Wu College of Information Science and Technology Beijing University of Chemical Technology Beijing China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

A mobile robot is one of the well-known nonholonomic systems. The genetic fuzzy + PI path tracking control applied to a mobile robot is presented. The proposed controller composes of two fuzzy + PI controllers which are employed to control the angular velocity together, and one fuzzy + PI controller that is utilized to adjust the speed of mobile robot solely. Moreover, the fuzzy controller is designed to track reference path in approaching phase and PI controller is operated to diminish the tracking error in stable phase. In order to obtain better tracking performance, Genetic algorithm (GA) is used to optimize controller parameters. Finally, computer simulation results are given to illustrate the effectiveness of the proposed control scheme.

关键词： PI control Computer simulation Genetics Angular velocity Mobile robots Tuning Optimization

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A comparative study of redundant feature detection based feature selection methods

A comparative study of redundant feature detection based fea...

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International Conference on Computer, Information and Telecommunication systems (CITS)

作者： Xue-Qiang Zeng Qian-Sheng Chen Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Computer Center Nanchang University Nanchang China

As a high dimensional problem, analysis of largescale data sets is a challenging task, where many weakly relevant or redundant features hurt generalization performance of classification models. In order to solve this problem, many effective feature selection methods have proposed to eliminate redundant features in recent years. However, the comparative performances of these redundant feature detection based methods have not been reported yet, which makes the choice of feature selection method relatively difficult for many real applications. The paper presents a novel comparative study of redundant feature detection based feature selection methods. Experiments on several benchmark data sets demonstrate the comparative performances of some state-of-the-arts methods. Based on the extensive empirical results, the minimum Redundancy-Maximum Relevance (mRMR) method has been found to be the best one among all compared feature selection models.

关键词： Breast Colon Lungs Redundancy

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