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作者： Ling, Qing Liu, Yaohua Shi, Wei Tian, Zhi Department of Automation University of Science and Technology of China Hefei230026 China Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Electrical and Computer Engineering George Mason University FairfaxVA22030 United States

In this paper, we propose a weighted alternating direction method of multipliers (ADMM) to solve the consensus optimization problem over a decentralized network. In the proposed algorithm, every node holds its local objective function, exchanges its current iterate with a subset of neighbors, carries on local computation, and eventually reaches an optimal and consensual solution that minimizes the summation of the local objective functions. Compared with the conventional ADMM that is popular in decentralized network optimization, the weighted ADMM is able to reduce the communication cost spent in the optimization process through tuning the weight matrices, which assign beliefs on the neighboring iterates. We first prove convergence and establish linear convergence rate of the weighted ADMM. Second, we maximize the derived convergence speed and obtain the best weight matrices on a given topology. Third, observing that exchanging information with all the neighbors is expensive, we maximize the convergence speed while limit the number of communication arcs. This strategy finds a subset of arcs within the underlying topology to fulfill the optimization task while leads to a favorable tradeoff between the number of iterations and the communication cost per iteration. Numerical experiments demonstrate advantages of the weighted ADMM over its conventional counterpart in expediting the convergence speed and reducing the communication cost. © 1991-2012 IEEE.

关键词： Topology

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A Data Driven Approach for Resting-state EEG signal Classificition of Schizophrenia with Control Participants Using Random Matrix Theory

arXiv

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arXiv 2017年

作者： Liu, Haichun Zhang, TianHong Ye, Yumeng Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiaotong University Shanghai200240 China Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Resting state electroencephalogram (EEG) abnormalities in clinically high-risk individuals (CHR), clinically stable first-episode patients with schizophrenia (FES), healthy controls (HC) suggest alterations in neural oscillatory activity. However, few studies directly compare these anomalies among each types. Therefore, this study investigated whether these electrophysiological characteristics differentiate clinical populations from one another, and from non-psychiatric controls. To address this question, resting EEG power and coherence were assessed in 40 clinically high-risk individuals (CHR), 40 first-episode patients with schizophrenia (FES), and 40 healthy controls (HC). These findings suggest that resting EEG can be a sensitive measure for differentiating between clinical *** paper proposes a novel data-driven supervised learning method to obtain identification of the patients mental status in schizophrenia research. According to Marchenko-Pastur Law, the distribution of the eigenvalues of EEG data is divided into signal subspace and noise subspace. A test statistic named LES that embodies the characteristics of all eigenvalues is adopted. different classifier and different feature(LES test function) are selected for experiments, we have shown that using von Neumann Entropy as LES test function combine with SVM classifier could obtain the best average classification accuracy during three classification among HC, FES and CHR of Schizophrenia group with EEG signal. It is worth noting that the result of LES feature extraction with the highest classification accuracy is around 90% in two classification(HC compare with FES) and around 70% in three classification. Where the classification accuracy higher than 70% could be used to assist clinical diagnosis. Copyright © 2017, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Model predictive control for PV maximum power point tracking of single-phase subMultilevel Inverter

Model predictive control for PV maximum power point tracking...

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IEEE Power and Energy Conference at Illinois, PECI 2016

作者： Metry, Morcos Bayhan, Sertac Balog, Robert S. Rub, Haitham Abu Renewable Energy and Advanced Power Electronics Research Laboratory United States Department of Electrical and Computer Engineering Texas AandM University College StationTX United States Department of Electronics and Automation Gazi University Ankara Turkey Electrical and Computer Engineering Program Texas AandM University at Qatar Doha Qatar Qatar Environment and Energy Research Institute Hamad Bin Khalifa University Qatar Foundation Doha Qatar

ISBN: (纸本)9781509002610

Dynamic behavior of solar energy resource entails the need of robust controllers that can converge to the maximum power point (MPP) to maximize energy harvest. This paper explores an improved Perturb and Observe (P&O) technique that combines a fixed step model predictive controller (MPC), to speed up the control loop, applied to a boost converter. The proposed MPC Maximum Power Point Tracking (MPPT) technique is of higher efficacy and robustness over conventional MPPT. The improved MPCMPPT is tested for the first time on an MPC strategy of sevenlevel subMultilevel Inverter (sMI) using three power arms cascaded with the H-bridge inverter. Such topology brings about many sizable benefits such as reduced number of power switches and their gate drivers when compared to the traditional multilevel inverter. MPC is also used as the control strategy for the sMI to eliminate complexities in the space vector pulse width modulation (SVPWM) and overcome the weaknesses of the inner control loop performance. © 2016 IEEE.

关键词： Model predictive control

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Improvement of Resting-state EEG Analysis Process with Spectrum Weight-Voting based on LES

arXiv

引用

arXiv 2017年

作者： Ye, Yumeng Liu, Haichun Zhang, TianHong Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation and Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiaotong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Electroencephalography is a non-invasive technique for recording brain bioelectric activity, which has potential applications in various fields such as human-computer interaction and neuroscience. Among them, analysis of the risk of schizophrenia using EEG data is a relatively new research topic. However, there are many difficulties in analyzing EEG data, including its complex composition, low amplitude as well as low signal-to-noise ratio. Some of the existing methods of analysis are based on feature extraction and machine learning to differentiate the phase of schizophrenia (First-episode schizophrenia, Healthy controls or Clinical high-risk) that samples belong to. However, medical research requires the use of machine learning not only to give more accurate classification results, but also to give the results that can be applied to pathological studies. The main purpose of this study is to obtain the weight values as the representation of influence of each frequency band on the classification of schizophrenia phases on the basis of a more effective classification method using the LES feature extraction, and then the weight values are processed and applied to improve the accuracy of machine learning classification. We propose a method called weight-voting to obtain the weights of sub-bands features by using results of classification for voting to fit the actual categories of EEG data, and using weights for reclassification. Through this method, we can first obtain the influence of each band in distinguishing three schizophrenia phases, and analyze the effect of band features on the risk of schizophrenia contributing to the study of psychopathology. In addition, the weights applied to the original classifier can achieve the upgrade of the classification effect, which contributes to the BCI-assisted system of diagnosis and treatment. Our results show that there is a high correlation between the change of weight of low gamma band and the difference between HC, CHR an

关键词： Electroencephalography

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Nanoscale monitoring of drug actions on cell membrane using atomic force microscopy

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中国药理学报（英文版） 2015年第7期36卷 769-782页

作者： Mi LI Lian-qing LIU Ning XI Yue-chao WANG State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Department of Electrical and Computer Engineering Michigan State University East Lansing MI 48824 USA

Knowledge of the nanoscale changes that take place in individual cells in response to a drug is useful for understanding the drug action. However, due to the lack of adequate techniques, such knowledge was scarce until the advent of atomic force microscopy (AFM), which is a multifunctional tool for investigating cellular behavior with nanometer resolution under near-physiological conditions. In the past decade, researchers have applied AFM to monitor the morphological and mechanical dynamics of individual cells following drug stimulation, yielding considerable novel insight into how the drug molecules affect an individual cell at the nanoscale. In this article we summarize the representative applications of AFM in characterization of drug actions on cell membrane, including topographic imaging, elasticity measurements, molecular interaction quantification, native membrane protein imaging and manipulation, etc. The challenges that are hampering the further development of AFM for studies of cellular activities are aslo discussed.

关键词： atomic force microscopy single-cell technique nanometer scale drug-target interaction cell mechanics cell elasticity

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Learning dexterous manipulation for a soft robotic hand from human demonstrations

Learning dexterous manipulation for a soft robotic hand from...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Abhishek Gupta Clemens Eppner Sergey Levine Pieter Abbeel Department of Electrical Engineering and Computer Sciences University of California at Berkeley USA Robotics and Biology Laboratory Technische Universitat Berlin Germany

ISBN: (纸本)9781509037636

Dexterous multi-fingered hands can accomplish fine manipulation behaviors that are infeasible with simple robotic grippers. However, sophisticated multi-fingered hands are often expensive and fragile. Low-cost soft hands offer an appealing alternative to more conventional devices, but present considerable challenges in sensing and actuation, making them difficult to apply to more complex manipulation tasks. In this paper, we describe an approach to learning from demonstration that can be used to train soft robotic hands to perform dexterous manipulation tasks. Our method uses object-centric demonstrations, where a human demonstrates the desired motion of manipulated objects with their own hands, and the robot autonomously learns to imitate these demonstrations using reinforcement learning. We propose a novel algorithm that allows us to blend and select a subset of the most feasible demonstrations, which we use with an extension of the guided policy search framework that learns generalizable neural network policies. We demonstrate our approach on the RBO Hand 2, with learned motor skills for turning a valve, manipulating an abacus, and grasping.

关键词： Hand Abacus Motor Skills Grasp learning (artificial intelligence) Learning Does manipulate objects Human

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Flame detection based on spatio-temporal covariance matrix

Flame detection based on spatio-temporal covariance matrix

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Changjun Gu Dongying Tian Yang Cong Yanzhu Zhang Shuai Wang Automation and Electrical Engineering Department Shenyang Li gong University Shenyang China State Key Laboratory of Robotics Chinese Academy of sciences Shenyang China

ISBN: (纸本)9781509033652

Automatic fire flame detection is important for intelligent video surveillance. The background model and various color features are usually adopted for flame detection. In this paper, a fire flame detection method is developed by combining both background subtraction and region covariance. The color distribution method and background model with an adaptive background learning model are used to preprocess the image firstly. We then extract the space-temporal covariance matrix, which is used to fuse all the discriminative cues together. Finally we use support vector machine to classify fire scene. The proposed system is effective in detecting uncontrolled fire in complicated environment. Experiments based on several public fire video data sets are utilized to justify the effectiveness of our method.

关键词： Fires Image color analysis Covariance matrices Hidden Markov models Support vector machines Adaptation models Feature extraction

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Template-based human supervised robot task programming

Template-based human supervised robot task programming

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Xianchao Long Taskin Padir Robotics and Intelligent Vehicles Research Laboratory (RIVeR Lab) Department of Electrical and Computer Engineering Northeastern University Boston Massachussetts United States

ISBN: (纸本)9781509037636

Motions of a robot interacting with its environment can be described by a set of constraints. This paper introduces an approach, called motion template, which can quickly program and compose the constraints for the motion planner to generate the trajectory. Two types of motion templates, grasp and turn, are specifically described to explain the details of the technique. The reusability and shareability properties of the motion template are demonstrated using a variety of the motion planning applications across different robot platforms. A motion template framework is used to implement the motion template with the trajectory optimization.

关键词： jigs(templates) Robot trajectory optimization Programming

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Effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells investigated by atomic force microscopy

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Science China(Life Sciences) 2015年第9期58卷 889-901页

作者： LI Mi LIU LianQing XI Ning WANG YueChao XIAO XiuBin ZHANG WeiJing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Electrical and Computer Engineering Michigan State University Department of Lymphoma Affiliated Hospital of Military Medical Academy of Sciences

Cell mechanics plays an important role in cellular physiological activities. Recent studies have shown that cellular mechanical properties are novel biomarkers for indicating the cell states. In this article, temperature-controllable atomic force microscopy(AFM) was applied to quantitatively investigate the effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells. First, AFM indenting experiments were performed on six types of human cells to investigate the changes of cellular Young's modulus at different temperatures and the results showed that the mechanical responses to the changes of temperature were variable for different types of cancer cells. Second, AFM imaging experiments were performed to observe the morphological changes in living cells at different temperatures and the results showed the significant changes of cell morphology caused by the alterations of temperature. Finally, by co-culturing human cancer cells with human immune cells, the mechanical and morphological changes in cancer cells were investigated. The results showed that the co-culture of cancer cells and immune cells could cause the distinct mechanical changes in cancer cells, but no significant morphological differences were observed. The experimental results improved our understanding of the effects of temperature and cellular interactions on the mechanics and morphology of cancer cells.

关键词： atomic force microscopy mechanics cancer cell temperature cellular interactions

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Reconstruction of function block controllers based on test scenarios and verification

Reconstruction of function block controllers based on test s...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Daniil Chivilikhin Ilya Ivanov Anatoly Shalyto Valeriy Vyatkin Computer Technologies Laboratory ITMO University Saint Petersburg Russia Department of Computer Science Lulea Tekniska Universitet Sweden Department of Electrical Engineering and Automation Aalto University Finland

ISBN: (纸本)9781509028719

The paper addresses the problem of reverse engineering a function block (FB) in situations when its source code is either not available or is too complex to understand. The proposed approach builds up on a recent method for reconstructing FBs based on testing and a search-based optimization algorithm. In our work the method is augmented with candidate solution verification using the NuSMV model checker. Verification is done in a closed-loop way using a manually constructed surrogate model of the plant and environment.

关键词： Testing Optimization IEC Standards Input variables Control charts Error correction codes computers

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