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arXiv 2019年

作者： Di, Boya Zhang, Hongliang Song, Lingyang Li, Yonghui Han, Zhu Vincent Poor, H. Department of Electronics Engineering Peking University Beijing China Department of Computing Imperial College London London United Kingdom Department of Electronical and Computer Engineering University of Houston HoustonTX United States School of Electrical and Information Engineering University of Sydney Australia School of Engineering and Applied Science Princeton University NY United States

Reconfigurable intelligent surface (RIS) has drawn considerable attention from the research society recently, which creates favorable propagation conditions by controlling the phase shifts of the reflected waves at the surface, thereby enhancing wireless transmissions. In this paper, we study a downlink multi-user system where the transmission from a multi-antenna base station (BS) to various users is achieved by the RIS reflecting the incident signals of the BS towards the users. Unlike most existing works, we consider the practical case where only a limited number of discrete phase shifts can be realized by the finite-sized RIS. Based on the reflection-dominated one-hop propagation model between the BS and users via the RIS, a hybrid beamforming scheme is proposed and the sum-rate maximization problem is formulated. Specifically, the continuous digital beamforming and discrete RIS-based analog beamforming are performed at the BS and the RIS, respectively, and an iterative algorithm is designed to solve this problem. Both theoretical analysis and numerical validations show that the RIS-based system can achieve a good sum-rate performance by setting a reasonable size of RIS and a small number of discrete phase shifts. Copyright © 2019, The Authors. All rights reserved.

关键词： Iterative methods

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Adaptive morphological reconstruction for seeded image segmentation

arXiv

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arXiv 2019年

作者： Lei, Tao Jia, Xiaohong Liu, Tongliang Liu, Shigang Meng, Hongying Nandi, Asoke K. School of Electronical and Information Engineering Shaanxi University of Science and Technology Xi’an710021 China School of Computer Science Northwestern Polytechnical University Xi’an710072 China School of Electronical and Information Engineering Shaanxi University of Science and Technology Xi’an710021 China School of Computer Science University of Sydney Sydney Australia School of Computer Science Shaanxi Normal University Xi’an710119 China Department of Electronic and Computer Engineering Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom Department of Electronic and Computer Engineering Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Col- lege of Electronic and Information Engineering Tongji University Shanghai200092 China

—Morphological reconstruction (MR) is often employed by seeded image segmentation algorithms such as watershed transform and power watershed as it is able to filter seeds (regional minima) to reduce over-segmentation. However, MR might mistakenly filter meaningful seeds that are required for generating accurate segmentation and it is also sensitive to the scale because a single-scale structuring element is employed. In this paper, a novel adaptive morphological reconstruction (AMR) operation is proposed that has three advantages. Firstly, AMR can adaptively filter useless seeds while preserving meaningful ones. Secondly, AMR is insensitive to the scale of structuring elements because multiscale structuring elements are employed. Finally, AMR has two attractive properties: monotonic increasingness and convergence that help seeded segmentation algorithms to achieve a hierarchical segmentation. Experiments clearly demonstrate that AMR is useful for improving algorithms of seeded image segmentation and seed-based spectral segmentation. Compared to several state-of-the-art algorithms, the proposed algorithms provide better segmentation results requiring less computing time. Source code is available at https://***/SUST-reynole/AMR. Copyright © 2019, The Authors. All rights reserved.

关键词： Image segmentation

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A Weighted Dynamic Inverse Problem for electroencephalographic current density reconstruction

A Weighted Dynamic Inverse Problem for electroencephalograph...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： E. Giraldo J. S. Castaño-Candamil G. Castellanos-Dominguez Faculty of Electrical and Electronic Engineering Universidad Tecnológica de Pereira Colombia Electrical Electronical and Computing Engineering Department Universidad Nacional de Colombia sede Manizales

A Weighted Dynamic Inverse Problem Solution is proposed for electroencephalographic current density reconstruction. The method considers physiologically based models that takes both spatial and temporal dynamics into account and a weighting stage to obtain the covariance of the measurement equation from observations. The calculated weighting matrix is included in the cost function used to solve the dynamic inverse problem. Additionally, an iterative method for inverse problem solution is proposed which considers the time varying weighting matrix in the solution. In this way, a weighted dynamic inverse problem solution is proposed including a time varying weighting matrix. The method performance is analyzed in terms of standard error, projected error, and residual error for several SNRs by using simulated signals through complex dynamical models.

关键词： Brain models Inverse problems Covariance matrices Mathematical model Electroencephalography Current density

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Interference and shortest path optimization on a ZigBee sensors network application

Interference and shortest path optimization on a ZigBee sens...

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Int. Conf. on Applied, Numerical and Computational Mathematics, ICANCM'11, Int. Conf. on Computers, Digital Communications and computing, ICDCC'11, Int. Conference on Applied Social Science, Social Economy and Digital Convergence, IC-ASSSE-DC'11

作者： Jauregui, Fabio Guerrero, Rubén Rodríguez, Darwin Donoso, Yezid Department of Computing and Systems Engineering University of the Andes Bogotá Colombia Department of Electrical and Electronical Engineering University of the Andes Bogotá Colombia

ISBN: (纸本)9781618040305

This paper presents an application of Multi-objective optimization and evolutive algorithms in a ZigBee network to determine the optimal routing tree for transmission. In this research the interference among nearby networks and the number of hops were taken as objective functions. The multi-objetive evolutionary algorithm SPEA (Strength Pareto Evolutionary Algorithm is used for optimizing the model and to find the best solutions among several feasible ones. In addition, a suitable chromosome is defined with crossover and mutation operators and multi-objective performance metrics such as generational distance and spacing between others are evaluated. Finally a comparison between a numerical solution based on a mathematical model using weight sum method and MOEA solution is shown.

关键词： Zigbee

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Current density reconstruction from EEG based on a time varying nonlinear physiological model

Current density reconstruction from EEG based on a time vary...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： E. Giraldo G. Castellanos-Dominguez Faculty of Electrical and Electronic Engineering Physics and Computer Science Universidad Tecnológica de Pereira Colombia Electronical and Computing Engineering Department Universidad Nacional de Colombia Colombia

A new electroencephalographic current density reconstruction method is introduced using a physiologically based nonlinear modeling that describes better the dynamic behavior of the neural activity. In addition, time-variant parameters are considered into the model to capture the dynamics for normal and pathological states measured from signals. The method is implemented by Unscented Kalman filtering approach. The performance of the new method is evaluated (in terms of mean square error) by application to simulated EEG data over several noise conditions, and a considerable improvement over linear estimation approaches is found.

关键词： Brain modeling Electroencephalography Estimation Mathematical model Inverse problems Computational modeling Kalman filters

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Comparative analysis of time frequency representations for discrimination of epileptic activity in EEG signals

Comparative analysis of time frequency representations for d...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： J. D. Martínez-Vargas L. D. Avendaño-Valencia E. Giraldo G. Castellanos-Dominguez Universidad Nacional de Colombia Colombia Faculty of Electrical and Electronic Engineering Physics and Computer Science Universidad Tecnológica de Pereira Colombia Electrical Electronical and Computing Engineering Department Universidad Nacional de Colombia Colombia

Epilepsy is a brain pathology that affects approximately 40 million people in the world. The most utilized clinical test for epilepsy diagnose is the electroencephalogram (EEG). For this reason, nowadays are being developed multiple tools devised for automatic seizure detection on EEG signals. In this work, several approaches of TFR estimation for detection of epileptic events in EEG recordings are compared. Parametric (stochastic evolving and local estimation) TFR estimators as well as non-parametric (STFT, SPWV and CWT) are under study. Comparison is made according with the achieved performance using a recently proposed methodology for TFR based classification. Results show similar outcomings with all approaches for TFR estimation, achieving accuracy rates from 96 to 99%. Best performance was found for STFT and STTVAR approaches for TFR estimation.

关键词： Time frequency analysis Electroencephalography Estimation Accuracy Continuous wavelet transforms Brain modeling Databases

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Damage detection in vibration signals using non parametric time-frequency representations 24

Damage detection in vibration signals using non parametric t...

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24th International Conference on Noise and Vibration engineering, ISMA 2010, in conjunction with the 3rd International Conference on Uncertainty in Structural Dynamics, USD 2010

作者： Cardona-Morales, O. Orozco-Ángel, A. Castellanos-Domínguez, G. Universidad Nacional de Colombia-S.Manizales Department Electrical Electronical and Computing Engineering Manizales Colombia Universidad Tecnológica de Pereira Pereira Colombia

ISBN: (纸本)9789073802872

The vibration analysis is the most used tool for fault detection in rotating machines, thereby its low cost in comparison with others tool as ultrasound. This tool accomplished of digital signal processing is very powerful for make decisions and faults identification. Time-frequency (TF) representations are one of the most popular characterization methods for non-stationary vibration signals. Despite of their potential advantages, these representations suffer of large quantity of redundant and irrelevant data which makes them difficult to use for classification purposes. In this work, a methodology for reduction of irrelevant and redundant data is explored. This approach consists on removing irrelevant data, applying a relevance measure on the t-f plane that measures the dependence of each t-f point with the class labels. Results shows that the relevance measures increase the performance classification and the faults are totally differentiable.

关键词： Vibration analysis

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Reduction of irrelevant and redundant data from TFRs for EEG signal classification

Reduction of irrelevant and redundant data from TFRs for EEG...

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

作者： L. D. Avendaño-Valencia J. D. Martínez-Vargas E. Giraldo G. Castellanos-Domíngue Universidad Nacional de Colombia Sede Manizales Colombia Electrical and Electronic Engineering Universidad Tecnológica de Pereira Colombia Electrical Electronical and Computing Engineering Department Universidad Nacional de Colombia Sede Manizales Colombia

Time-frequency representations (TFR) are one of the most popular characterization methods for non-stationary biosignals. Despite of their potential advantages, these representations suffer of large quantity of redundant and irrelevant data which makes them difficult to use for classification purposes. In this work, a methodology for reduction of irrelevant and redundant data is explored. This approach consists on removing irrelevant data, applying a relevance measure on the t-f plane that measures the dependence of each t-f point with the class labels. Then, principal component analysis (PCA) and partial least squares (PLS) are used as non-supervised and supervised linear decomposition approaches to reduce redundancy of remaining t-f points. Results show that the proposed methodology improves the performance of classifier up to 3% when no relevance and redundancy on TFRs is reduced.

关键词： Principal component analysis Measurement uncertainty Correlation Electroencephalography Time frequency analysis Uncertainty Redundancy

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An Approach for the Implementation of Personalization Recommendation of Text Information Retrieval With TextCC

An Approach for the Implementation of Personalization Recomm...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Zhenya Zhang Shuguang Zhang Xufa Wang Shuangping Chen Hongmei Cheng MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology of China(USTC) Electronical Engineering & Information Science Department of USTC Statistics&Finance Department of USTC Computer Science Department of USTC Mathematics Department of Anhui Normal University

To implement personalization recommendation of text information retrieval(TR) based in user-focus,TextCC,a feed forward neural network for instantly classification is adopted to classify query results according to user-focuses of a user in the *** results show that the implementation of personalization recommendation with TextCC can lighten the user's burden induced by the work of filtering valid information from vast information in some degree while the time requirement of TR is satisfied very well.

关键词： Web An Approach for the Implementation of Personalization Recommendation of Text Information Retrieval With TextCC

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Certainty equivalence in constrained linear systems subject to stochastic disturbances

Certainty equivalence in constrained linear systems subject ...

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American Control Conference (ACC)

作者： I. Batina A.A. Stoorvogel S. Weiland Department of Electrical Engineering Mathematics and Computer Delft University of Technnology Delft Netherlands Department of Mathematics and Computing Science Eindhovan University of Technology Eindhoven Netherlands Control Systems Group Department of Electronical Engineering Eindhovan University of Technology Eindhoven Netherlands

A sufficient condition is provided under which the optimal controller of a constrained optimization problem can be synthesized by combining an optimal state estimator with an optimal static state feedback. An application of a model predictive controller is considered that involves both input and state constraints in a system that is subject to stochastic disturbances.

关键词： Linear systems Stochastic systems State feedback State estimation Control systems Optimal control Constraint optimization Q measurement Noise measurement Stochastic processes

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