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检索条件"机构=Dept. of Control and Computer Engineering"

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A new statistical approach for the extraction of adjacency matrix from effective connectivity networks

A new statistical approach for the extraction of adjacency m...

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2013 35th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2013

作者： Toppi, J. De Vico Fallani, F. Petti, M. Vecchiato, G. Maglione, A. Cincotti, F. Salinari, S. Mattia, D. Babiloni, F. Astolfi, L. Department of Computer Control and Management Engineering Univ. of Rome Sapienza Italy Dept. of Physiology and Pharmacology University of Rome Sapienza Italy Department of Anatomy Histology Forensic Medicine and Orthopedics University of Rome Sapienza Italy Fondazione Santa Lucia Hospital Rome Italy

ISBN: (纸本)9781457702167

Graph theory is a powerful mathematical tool recently introduced in neuroscience field for quantitatively describing the main properties of investigated connectivity networks. Despite the technical advancements provided in the last few years, further investigations are needed for overcoming actual limitations in the field. In fact, the absence of a common procedure currently applied for the extraction of the adjacency matrix from a connectivity pattern has been leading to low consistency and reliability of ghaph indexes among the investigated population. In this paper we proposed a new approach for adjacency matrix extraction based on a statistical threshold as valid alternative to empirical approaches, extensively used in Neuroscience field (i.e. fixing the edge density). In particular we performed a simulation study for investigating the effects of the two different extraction approaches on the topological properties of the investigated networks. In particular, the comparison was performed on two different datasets, one composed by uncorrelated random signals (null-model) and the other one by signals acquired on a mannequin head used as a phantom (EEG null-model). The results highlighted the importance to use a statistical threshold for the adjacency matrix extraction in order to describe the real existing topological properties of the investigated networks. The use of an empirical threshold led to an erroneous definition of small-world properties for the considered connectivity patterns. © 2013 IEEE.

关键词： Extraction

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Nonlinear control Design for the Photovoltaic Isolated-Port Architecture with Submodule Integrated Converters

Nonlinear Control Design for the Photovoltaic Isolated-Port ...

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IEEE Energy Conversion Congress and Exposition

作者： Yoash Levron Daniel Clement Dragan Maksimovic Carlos Olalla Dept. of Electrical Computer and Energy Engineering University of Colorado at Boulder Boulder CO 80309-0425 USA Dept. of Electronic Electrical and Automatic Control Engineering Universitat Rovira i Virgili Tarragona Spain

ISBN: (纸本)9781479903375

Differential power processing (DPP) isolated-port architecture with submodule integrated converters (subMICs) enables improved energy capture in photovoltaic (PV) power systems. This paper describes a control scheme for flyback subMICs operating in discontinuous conduction mode (DCM). The duty-cycle is driven in proportion to a voltage error, with no further processing, thus eliminating the need to measure or to control the current explicitly. The approach is well suited for very simple, analog PWM controller implementation, but the resulting control loops become nonlinear. The system stability is demonstrated using the Lyapunov stability theorem. Experimentally measured module-level efficiency is greater than 95% for a 72-cell PV module having 3 substrings with solar irradiation of 80%, 60% and 40%, respectively.

关键词： respectively stability substrings submodule PHOTOVOLTAIC substring voltage error design control Converters Energy capture control ring System stability solar radiation Solar Irradiance nonlinear control Lyapunov methods Building construction ARCHITECTURE

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Performance analysis for high-speed railway communication network using stochastic network calculus

Performance analysis for high-speed railway communication ne...

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5th IET International Conference on Wireless, Mobile and Multimedia Networks, ICWMMN 2013

作者： Li, Ying Lei, Lei Zhong, Zhangdui Lin, Siyu School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 China State Key Lab. of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China Dept. of Electrical and Computer Engineering University of Victoria Victoria BC V8P 5C2 Canada

ISBN: (纸本)9781849197267

High-speed railway (HSR) wireless communication network has won a great development in recent years. However, due to its unique characteristics, such as high speed, fixed mobility track, special traffic, frequent handover and bandwidth constraints, it is quite a challenge to carry out the performance analysis on HSR. In this paper, we derive the backlog and delay bounds for HSR communication network by using stochastic network calculus (SNC) with moment generating functions (MGFs). SNC is a highly useful tool in packet switched network performance analysis since 1990s. Different from the previous studies about SNC which mostly concentrate on general low-speed, traditional public communication network, we take the varying small-scale fading and large-scale fading into consideration by means of a novel multi-dimension finite-state Markov channel (FSMC) model. We elaborate the differences in packet-level channel model, traffic model of train control information and performance metrics in HSR communication network. Particularly, the backlog and delay bounds of HSR with different packet arrival rates and violation probabilities are derived when train travels from the cell center to the cell edge. What is more, the numerical results can help to provide a guideline for designing the proper violation probabilities and arrival rates to different types of traffic in HSR communication network.

关键词： Calculations

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： M Petti J Toppi F Pichiorri F Cincotti S Salinari F Babiloni L Astolfi D Mattia Department of Computer Control and Management Engineering Univ. of Rome “Sapienza” Fondazione Santa Lucia Rome Italy Department of Computer Control and Management Engineering Univ. of Rome “Sapienza” Rome Italy Dept. of Physiology and Pharmacology of the University of Rome “Sapienza”

Recent studies have investigated changes in the human brain network organization during the normal aging. A reduction of the connectivity between brain areas was demonstrated by combining neuroimaging technologies and graph theory. Clustering, characteristic path length and small-worldness are key topological measures and they are widely used in literature. In this paper we propose a new methodology that combine advanced techniques of effective connectivity estimation, graph theoretical approach and classification by SVM method. EEG signals recording during rest condition from 20 young subjects and 20 mid-aged adults were studied. Partial Directed Coherence was computed by means of General Linear Kalman Filter and graph indexes were extracted from estimated patterns. At last small-worldness was used as feature for the SVM classifier. Results show that topological differences of brain networks exist between young and mid-aged adults: small-worldness is significantly different between the two populations and it can be used to classify the subjects with respect to age with an accuracy of 69%.

关键词： Indexes Estimation Support vector machines Feature extraction Aging Sociology Statistics

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Hierarchical fuzzy approaches for a piloted Quality Management System

Hierarchical fuzzy approaches for a piloted Quality Manageme...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： H. Ben Mahmoud R. Ketata T. Ben Romdhane S. Ben Ahmed Dept. of Physics and Instrumentation Engineering INSAT: National Institute of Applied Science and Technology Dept. of Physics and Instrumentation Engineering ICOS: Research Unit on Intelligent Control Tunis Tunisia Dept. of Physics and Instrumentation Engineering MOSIC Research Unit on Methods and Tools for Complex Computer Systems Tunis Tunisia

In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management System (QMS). These approaches have been applied for real company which presents a major problem for controlling the quality level of production. HFS structure has reduced complexity in the number of input and output meta-levels of hierarchy. Also NFHH model has presented better performance in terms of precision and number of parameters without losing the universal approximation property of neural networks (NN) and fuzzy systems.

关键词： Companies IP networks Production Complexity theory Fuzzy logic Artificial neural networks Pragmatics

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On-line semantic mapping

On-line semantic mapping

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International Conference on Advanced Robotics (ICAR)

作者： E. Bastianelli D. D. Bloisi R. Capobianco F. Cossu G. Gemignani L. Iocchi D. Nardi Dept. of Computer Control and Management Engineering Sapienza University of Rome Italy Universita degli Studi di Roma La Sapienza Roma Lazio IT

Human Robot Interaction is a key enabling feature to support the introduction of robots in everyday environments. However, robots are currently incapable of building representations of the environments that allow both for the execution of complex tasks and for an easy interaction with the user requesting them. In this paper, we focus on semantic mapping, namely the problem of building a representation of the environment that combines metric and symbolic information about the elements of the environment and the objects therein. Specifically, we extend previous approaches, by enabling on-line semantic mapping, that permits to add to the representation elements acquired through a long term interaction with the user. The proposed approach has been experimentally validated on different kinds of environments, several users, and multiple robotic platforms.

关键词： Semantics Robot sensing systems Navigation Grounding Buildings Measurement

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Silhouette based gait recognition based on the area features using both model free and model based approaches

Silhouette based gait recognition based on the area features...

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IEEE Conference on Technologies for Homeland Security

作者： Arihant Kochhar Divyesh Gupta Madasu Hanmandlu Shantaram Vasikarla Dept. of Computer Science Columbia University New York NY Dept. of Control and Inst. N. S. Institute of Technology New Delhi India Dept. of Electrical Engineering Indian Institute of Technology New Delhi India Dept. of Computer Science California State University Northridge CA

Gait recognition has lately attracted the attention of a plethora of computer vision and biometric systems researchers. It offers advantages like non-invasiveness, data acquisition from a distance and low resolution. The geometric area between the limbs derived from the spatial-temporal silhouettes serves as an effective feature that is capable of differentiating subjects. Both model-based and model-free approaches are tried while extracting features for the gait recognition. Support Vector Machine (SVM) classifier is used for training the features from silhouettes of the known gaits and identifying the unknown gaits based on the same features. Experimentation on the silhouette samples of publicly available CASIA database vindicates the supremacy of the model based approach over the model free approach.

关键词： Feature extraction Support vector machines Legged locomotion Gait recognition Biological system modeling Shape Analytical models

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Current Source Rectifiers in Discontinuous Conduction Modes of Operation

Current Source Rectifiers in Discontinuous Conduction Modes ...

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IEEE Energy Conversion Congress and Exposition

作者： Robert M. Cuzner Giri Venkataramanan DRS Technologies DRS Power and Control Technologies Milwaukee WI USA University of Wisconsin-Madison Dept. of Electrical and Computer Engineering Madison WI USA

ISBN: (纸本)9781479903375

While operation of the three phase Current Source Rectifier (CSR) for ac-to-dc conversion using phase control or low frequency pulse control is well established in a wide variety of applications, CSR realization using high frequency Pulse-Width-Modulation (PWM) control is being studied recently as a potentially competitive alternative to a Voltage Source Rectifier (VSR). In the CSR reverse blocking gate turn-off switches are realized using series connected diodes, which prevent any reversal of the dc link current. A significant consequence of this limitation occurs at light load conditions. The dc link inductor current enters discontinuous mode of operation and leads to loss of control of output voltage and highly distorted input current, which compromises the potential advantages of the approach. This paper characterizes the CSR while operating in discontinuous conduction mode and proposes a modulation strategy which restores control of output voltage and ensures nearly sinusoidal current at light loads. Simulation and hardware results are provided for a 3kW laboratory scale prototype system.

关键词： output voltage Rectifiers Surgery discontinuous conduction mode Current sources discontinuous mode lighter load phase control pulse frequency Pulse width modulation DC link current DC conversion Switches operation mode conductive pattern

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A Decentralized Framework of Unit Commitment for Future Power Markets

A Decentralized Framework of Unit Commitment for Future Powe...

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IEEE Power and Energy Society General Meeting

作者： Mingyang Li Peter B. Luh Department of Control and Computer Engineering North China Electric Power University Beijing 102206 P. R. China Dept. of Electrical & Computer Engineering University of Connecticut Storrs CT 06269-2157 USA

ISBN: (纸本)9781479913022

Participants in future power markets will include many new entities brought by the emerging Smart Grid technologies. Such entities tend to behave autonomously to maximize their own benefits without revealing their detailed information, making it difficult to centrally clear the unit commitment based markets considering the security constraints coupled among entities. This paper presents a two level decentralized framework for solving the day-ahead unit commitment problem. On the lower level, each entity solves its own problem to optimize its benefits under the guidance of locational electricity prices, and sends the results to a bus coordinator. On the upper level, coordinators communicate with their neighbours to update the prices by using a distributed subgradient method. It is proved that with probability 1, the method will lead to a consensus on prices among all buses so that the market is cleared. D1ustrative examples are provided to demonstrate the effectiveness of our framework.

关键词： Power market unit commitment decentralized framework Lagrangian Relaxation distributed subgradient method power markets Unit commitment Prices Smart grids Motor buses Decentralized Frameworks Coordinator

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Self-explanatory Convex Sparse Representation for Image Classification

Self-explanatory Convex Sparse Representation for Image Clas...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Bao-Di Liu Yu-Xiong Wang Bin Shen Yu-Jin Zhang Yan-Jiang Wang Wei-Feng Liu College of Information and Control Engineering China University of Petroleum Qingdao 266580 China School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 USA Dept. of Computer Science Purdue University West Lafayette IN 47907 USA Dept. of Electronic Engineering Tsinghua University Beijing 100084 China

ISBN: (纸本)9781479906505

Sparse representation technique has been widely used in various areas of computer vision over the last decades. Unfortunately, in the current formulations, there are no explicit relationship between the learned dictionary and the original data. By tracing back and connecting sparse representation with the K-means algorithm, a novel variation scheme termed as self-explanatory convex sparse representation (SCSR) has been proposed in this paper. To be specific, the basis vectors of the dictionary are refined as convex combination of the data points. The atoms now would capture a notion of centroids similar to Kmeans, leading to enhanced interpretability. Sparse representation and K-means are thus unified under the same framework in this sense. Besides, an appealing property also emerges that the weight and code matrices both tend to be naturally sparse without additional constraints. Compared with the standard formulations, SCSR is easier to be extended into the kernel space. To solve the corresponding sparse coding subproblem and dictionary learning subproblem, block-wise coordinate descent and Lagrange multipliers are proposed accordingly. To validate the proposed algorithm, it is implemented in image classification, a successful applications of sparse representation. Experimental results on several benchmark data sets, such as UIUC-Sports, Scene 15, and Caltech-256 demonstrate the effectiveness of our proposed algorithm.

关键词： Convex hull Sparse representation Coordinate descent Image classification Image classification sparse representation convex hull images computer vision Dictionaries as Topic Convexity

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