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Consensus tracking of general linear multi-agent systems: fast sliding-mode algorithms

Consensus tracking of general linear multi-agent systems: fa...

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第三十二届中国控制会议

作者： Liu Huiyang Cheng Long Tan Min Hou Zengguang Wang Yunpeng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479900305

This paper solves distributed consensus tracking problems where the task is to make the multi-agent network, with each agent described by a general linear dynamics, to reach consensus with a leader whose control input is nonzero and not available to any followers. A set of sliding mode surfaces are defined and then fast sliding mode controllers are designed for both reduced order and non-reduced order cases. It is shown that all the trajectories exponentially converge to the sliding mode surfaces in a finite time if the leader has a directed path to at least one of the followers in a strongly connected and detailed balanced directed interaction graph and the leader’s control input is bounded. The control Lyapunov function for exponential finite time stability, motivated by the fast terminal sliding mode control, is used to prove the reachability of the sliding mode surfaces. Simulation examples are given to illustrate the theoretical results.

关键词： Multi-agent systems cooperative control fast terminal sliding mode consensus exponential finite-time

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Optimal Formation of Robots by the Continuous-Discrete PSO Algorithm in Three Dimensional Space

Optimal Formation of Robots by the Continuous-Discrete PSO A...

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第26届中国控制与决策会议

作者： Jun Liu Hongbin Ma Tianyun Shi Ping Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Institute of Computing Technologies Chinese Academy of Railway Sciences

ISBN: (纸本)9781479937097

This paper mainly provides and develops a new continuous-discrete PSO algorithm for handling with the optimal formation problem in the three dimensional space. For one class of formation problem with the particular constraints, it is shown that the center of the desired shape is determined and equal to the center of the initial shape by utilizing the Lagrangian method. From the perspective of efficiency, the main task of the continuous-discrete PSO algorithm, short for CDPSO, is to search for some key parameters and to minimize the distance of all robots from the initial shape to the desired shape. To demonstrate the effectiveness of the new CDPSO algorithm, numerical results chiefly concentrate on the optimal helicopters formation from the initial shape to the desired shape in the three dimensional space and the typical shape conversion from the two-dimensional space to the three-dimensional space.

关键词： Optimal formation Robots Lagrangian method Continuous-Discrete PSO algorithm

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Characterizing emotion entrainment in social media

Characterizing emotion entrainment in social media

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Saike He Xiaolong Zheng Xiuguo Bao Hongyuan Ma Daniel Zeng Bo Xu Changliang Li Hongwei Hao State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China CNCERT/CC Beijing China Department of Management Information Systems University of Arizona Tucson AZ USA Institute of Automation Chinese Academy of Sciences Beijing China

The sociological theory of entrainment accounts for the synchronization of human rhythmic modalities through social interactions: they coordinate in a variety of dimensions including linguistic styles, facial expressions, music pace, applause, and so on. Though highly relevant, emotion entrainment has received little attention to date. In addition, most previous studies on entrainment are done through small scale or controlled laboratory studies. In this paper, we investigate emotion entrainment in the context of online social media. To the best of our knowledge, this is the first time that emotion entrainment has been examined on a large scale, real world setting. For this purpose, we propose a framework that can model entrainment phenomenon and measure its effect. Our framework differentiates from previous research by its model-free essential and discerning in entrainment directions. These traits enable us to model entrainment dynamics under few assumptions, and distinguish emotion flow of entrainment. In our studies, we investigate entrainment patterns under different emotion states, i.e. positive, neutral and negative. We discover that entrainments under different emotions all follow a power law distribution. Besides, people are willing to entrain to others under positive emotion, and users with positive emotion are more likely to be entrained. By inspecting the interactions between entrainment and emotion, we reveal that entrainment has an effect of negotiating different emotion types toward an even distribution.

关键词： Entropy Mood Media Blogs Markov processes Conferences Social network services

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Ranking Online Memes in Emergency Events Based on Transfer Entropy

Ranking Online Memes in Emergency Events Based on Transfer E...

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IEEE Joint Intelligence and Security Informatics Conference (JISIC)

作者： Saike He Xiaolong Zheng Xiuguo Bao Hongyuan Ma Daniel Zeng Bo Xu Guanhua Tian Hongwei Hao State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China CNCERT/CC Beijing China Department of Management Information Systems University of Arizona Tucson AZ USA Institute of Automation Chinese Academy of Sciences Beijing China

The rapid proliferation of online social networks has greatly boosted the dissemination and evolution of online memes, which can be free text, trending catchphrase, or micro media. However, this information abundance is exceeding the capability of the public to consume it, especially in unusual situations such as emergency management, intelligence acquisition, and crime analysis. Thus, there calls for a reliable approach to rank meme appropriately according to its influence, which will let the public focus on the most important memes without sinking into the information flood. However, studying meme in any detail on a large scale proves to be challenging. Previous bottom-up approaches are often highly complex, while the more recent top-down network analysis approaches lack detailed modeling for meme dynamics. In this paper, we first present a formal definition for meme ranking task, and then introduce a scheme for meme ranking in the context of online social networks (OSN). To the best of our knowledge, this is the first time that memes have been ranked in a model-free manner. Empirical results on two emergency events indicate that our scheme outperforms several benchmark approaches. This scheme is also robust by insensitive to sample rate. In light of the scheme's fine-grain modeling on meme dynamics, we also reveal two key factors affecting meme influence.

关键词： Entropy Benchmark testing Social network services Robustness Security Media

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Using Web Data to Enhance Traffic Situation Awareness

Using Web Data to Enhance Traffic Situation Awareness

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17th International IEEE Conference on Intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Xiao Wang Ke Zeng Xue-Liang Zhao Fei-Yue Wang Qingdao Academy of Intelligent Industries State Key Lab of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences school of electronic and information engineering Xi’an Jiaotong University

With the ubiquity of mobile communication devices,people experiencing traffic jams share real-time information and interact with each other on social media sites,which provide new channels to monitor,estimate and manage traffic *** this paper,we use natural language processing and data mining technologies to extract traffic jam related information from ***,analyze the content of people’s talk to discover the "talking point" of people when facing traffic jams,and to provide data support for relevant authorities to make successful and effective decisions for real-time traffic jam response and management.

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A Robust Road Segmentation Method Based on Graph Cut with Learnable Neighboring Link Weights

A Robust Road Segmentation Method Based on Graph Cut with Le...

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17th International IEEE Conference on Intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Jun Yuan Shuming Tang Fei Wang Hong Zhang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences High-Tech Innovation Engineering Center Institute of AutomationChinese Academy of Sciences Institute of Artificial Intelligence and Robotics of Xi'an Jiaotong University School of Information Engineering Minzu University of China

Road region detection is a crucial functionality for road following in advanced driver assistance systems(ADAS).To address the problem of environment interference in road segmentation through a monocular vision approach,a novel graph-cut based method is proposed in this *** novelty of this proposal is that weights of neighboring links(n-links) in a s-t graph are estimated by Multilayer Perceptrons(MLPs) rather than calculating by the neighboring contrast simply in previous graph-cut based *** n-link weights by MLPs reinforces the ability of graph-cut based road segmentation algorithms to tolerate the complex and changeable appearance of road ***,the Gentle Ada Boost algorithm is integrated into the graph-cut framework to estimate the terminal link(t-link) weights in the s-t *** are conducted to show the robustness and efficiency of the proposed method.

关键词： image A Robust Road Segmentation Method Based on Graph Cut with Learnable Neighboring Link Weights Graph

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A two-stage fuzzy budget allocation model in search auctions

A two-stage fuzzy budget allocation model in search auctions

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Rui Qin Yong Yuan Juanjuan Li The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479960590

Budget optimization is an important issue faced by advertisers in search auctions, and has significant impact on the design of various advertising strategies. Given a limited budget on a search market during a certain period, an advertiser has to distribute her budget to a series of sequential temporal slots (i.e., days, weeks, or months), during which advertisers must avoid the budget being used up quickly, so as to keep the budget for potential clicks with better performance in the future. Considering the optimal budgets over these temporal slots as fuzzy variables, we establish a two-stage fuzzy budget allocation model, and use particle swarm optimization (PSO) algorithm to solve it in case when these optimal budgets are characterized by discrete fuzzy variables. We also conduct experiments to validate our model and algorithm. The experimental results show that our model can outperform other five budget allocation strategies in terms of reducing the revenue loss of the advertiser.

关键词： Artificial intelligence

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EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation

EEG-based classification of upper-limb ADL using SNN for act...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Jin Hu Zeng-Guang Hou Yi-Xiong Chen Nikola Kasabov Nathan Scott State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

Repetitive activities of daily living (ADL) and robotic active training are commonly practised in the rehabilitation of paralyzed patients, both of which have been proven rather effective to recover the locomotor function of impaired limbs. ADL classification based on electroencephalogram (EEG) is of great significance to perform active robotic rehabilitation for patients with complete spinal cord injury (SCI) who lose locomotion of affected limbs absolutely, where surface electromyography (sEMG) or active force signal can hardly be detected. It is a challenge to achieve a satisfying result in neuro-rehabilitation robotics using EEG signals due to the high randomness of the EEG data. A classification method is proposed based on spiking neural networks (SNN) to identify the upper-limb ADL of three classes with 14-channel EEG data. The continuous real-number signals are firstly encoded into spike trains through Ben's Spike Algorithm (BSA). The generated spikes are then submitted into a 3-D brain-mapped SNN reservoir called NeuCube trained by Spike Timing Dependant Plasticity (STDP). Spike trains from all neurons of the trained reservoir are finally classified using one version of dynamic evolving spiking neuron networks (deSNN) - deSNNs. Classifications are presented with and without NeuCube respectively on the same EEG data set. Results indicate that using the reservoir improves identification accuracy which turns out pretty promising despite that EEG data is highly noisy, low frequently sampled, and only from 14 channels. The classification technique reveals a great potential for the further implementation of active robotic rehabilitation to the sufferers of complete SCI.

关键词： Neurons Electroencephalography Training Robot kinematics Encoding Reservoirs

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Modeling interactions between low-level and high-level features for human action recognition

Modeling interactions between low-level and high-level featu...

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作者： Zhou, Wen Wang, Chunheng Xiao, Baihua Zhang, Zhong Shao, Yunxue State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

Recognizing human action in complex scenes is a challenging problem in computer vision. Some action-unrelated concepts, such as camera position features, could significantly affect the appearance of local spatio-temporal features, and therefore the performance of low-level features based methods degrades. In this letter, we define the action-unrelated concept: the position of camera as high-level features. We observe that they can serve as a prior to local spatio-temporal features for human action recognition. We encode this prior by modeling interactions between spatio-temporal features and camera position features. We infer camera position features from local spatio-temporal features via these interactions. The parameters of this model are estimated by a new max-margin algorithm. We evaluate the proposed method on KTH, IXMAS and Youtube actions datasets. Experimental results show the effectiveness of the proposed method. © 2013 The institute of Electronics, Information and Communication Engineers.

关键词： Cameras

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Index Modulated OFDM with Interleaved Grouping for V2X Communications

Index Modulated OFDM with Interleaved Grouping for V2X Commu...

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17th International IEEE Conference on Intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Xiang Cheng Miaowen Wen Liuqing Yang Yuke Li School of Electronics Engineering and Computer Science Peking University National Mobile Communications Research Laboratory Southeast University School of Electronic and Information Engineering South China University of Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

The rapid penetration of intelligent transportation systems（ITS） into the conventional transportation infrastructure urgently calls for high spectral efficiency high reliability communication technology for vehicle-to-vehicle and vehicle-to-infrastructure（V2X） *** orthogonal frequency division multiplexing（OFDM） is widely considered as a promising candidate for such applications,in this paper we propose a novel variation of OFDM for improved spectral efficiency as well as enhanced reliability in V2 X channels with correlated frequency-selective fading and inevitable Doppler *** proposed scheme is built upon a recently emerging technique termed as index modulated（IM-）***,different from the existing localized subcarrier grouping,we propose interleaved subcarrier *** then carry out analytical and simulated comparisons to demonstrate the merits of this new scheme in terms of both the bit error rate（BER）performance and the maximum achievable rate（MAR） of the overall system,in V2 X channels.

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