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Sensorless direct torque control of five-phase induction motor drives

Sensorless direct torque control of five-phase induction mot...

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Annual Conference of Industrial Electronics Society

作者： B. S. Khaldi H. Abu-Rub A. Iqbal R. Kennel M. O. Mahmoudi D. Boukhetala Department of Electrical Engineering Faculty of Science and Engineering Djelfa University Algeria Laboratory of Process Control National Polytechnic School Algiers Algeria Institute for Electrical Drive Systems and Power Electronics Technische Universität München Munich Germany Department of Electrical & Computer Engineering Texas A&M University at Qatar Doha Qatar Department of Electrical Engineering College of Engineering Qatar University Qatar Department of Electrical Engineering Aligarh Muslim University Aligarh India

This paper presents a simple and novel sensorless scheme for five-phase induction motor control. The power measurement is used for speed computation. The drive is controlled using direct torque control (DTC). Speed sensorless control scheme is tested under speed variation and load changes. The control method is simulated and implemented in real time on the DS1103 board.

关键词： Vectors Stators Torque Rotors Induction motors Torque control Electromagnetics

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PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COGNITIVE RADIO systems WITH INTERFERENCE CONSTRAINTS

PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COG...

引用

2011 4th IEEE International Conference on Broadband Network and Multimedia Technology

作者： Saeed Motiian Mohammad Aghababaie Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Colleague of EngineeringUniversity of TehranTehran 14399-57131Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences(IPM)Tehran 19548-56316 Iran Image Analysis Laboratory Radiology DepartmentHenry Ford HospitalDetroitMichigan 48202USA

Cognitive radio is used for enhancement of spectrum *** many works have been accomplished on the power allocation of cognitive radio,limited efforts have considered evolutionary *** this paper,we study this problem in the cognitive radio networks where interference constraints are defined for protection of quality of service（QoS）for both primary and secondary *** defined as functions of the signal-to-interference-plus-noise ratio（SINR） are matched for each secondary user which meets Nash’s *** general,the region of utilities that meets the constraints is *** is possible to make simplifications,generate a convex region,and then use common convex optimization approaches to obtain a ***,Particle Swarm Optimization（PSO）does not need such simplifications and thus its results are superior to those of the convex optimization *** is an evolutionary algorithm based on social intelligence,utilized in many optimization *** is a global optimizations algorithm that does not require the objective function be differentiable as required in classic optimization methods.

关键词： Cognitive radio Power allocation Particle Swarm Optimization（PSO）.

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System design and implementation of social interactive robot Nancy

System design and implementation of social interactive robot...

引用

International Conference on Information Sciences and Interaction Sciences (ICIS)

作者： Shuzhi Sam Ge Chun Fui Liew Yanan Li Institute of Intelligent Systems University of Electronic Science and Technology Chengdu China Social Robotics Laboratory Interactive Digital Media Institute and Department of Electrical and Computer Engineering National University of Singapore Singapore Social Robotics Laboratory Interactive Digital Media Institute and NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore

This paper presents a social interactive robot Nancy that has been developed in Social Robotics laboratory, National University of Singapore. Fundamentally different from factory robots, Nancy's design focuses on social interaction and social intelligent system. The design objectives and consideration are examined in the beginning, followed by the description of hardware and software architectures. Contrast to current existing social robots, Nancy has a graphical user interface (GUI), which acts as an additional channel for human-robot interaction. This GUI helps users to have a better understanding of Nancy's internal states and hence make users feel more comfortable during the interaction with Nancy. Visitors' interaction experience with Nancy is discussed together with Nancy's social skills.

关键词： Robots Graphical user interfaces Servomotors Speech Universal Serial Bus Face Hardware

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Gaussian Mixture PHD Smoother for Jump Markov Models in Multiple Maneuvering Targets Tracking

Gaussian Mixture PHD Smoother for Jump Markov Models in Mult...

引用

2011 American control Conference (ACC)

作者： Wenling Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper presents a Gaussian mixture probability hypothesis density (GM-PHD) smoother for tracking multiple maneuvering targets that follow jump Markov models. Unlike the generalization of the multiple model GM-PHD filters, our aim is to approximate the dynamics of the linear Gaussian jump Markov system (LGJMS) by a best-fitting Gaussian (BFG) distribution so that the GM-PHD smoother can be carried out with respect to an approximated linear Gaussian system. Our approach is inspired by the recognition that the BFG approximation provides an accurate performance measure for the LGJMS. Furthermore, the multiple model estimation is avoided and less computational cost is required. The effectiveness of the proposed smoother is verified with a numerical simulation.

关键词： Target tracking Approximation methods Markov processes Covariance matrix Smoothing methods Radar tracking Computational efficiency

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Adaptive Iterative Learning control for Uncertain Delay systems Based on Model Matching Technique

Adaptive Iterative Learning Control for Uncertain Delay Syst...

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2011 American control Conference (ACC)

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

In this paper, an adaptive iterative learning control (ILC) scheme is proposed for trajectory tracking of uncertain delay systems based on model matching technique. The reference model is a delay system operating over in a finite time interval. An iterative model matching controller is designed and an iteration domain adaptive law is chosen to estimate the unknown parameters. It shows that the model matching technique can be applied in a straightforward method to ILC problem. A simulation example is included to illustrate the designed scheme.

关键词： Adaptation models Polynomials Adaptive systems Delay effects Delay systems

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

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Middle East Conference on Biomedical engineering (MECBME)

作者： M. Parsa Hosseini Hamid Soltanian-Zadeh Shahram Akhlaghpoor Department of Electrical Engineering Islamic Azad University Tehran Iran Department of Radiology Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system.

关键词： Lungs Computed tomography Diseases Image segmentation Biomedical imaging Gaussian distribution

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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

引用

Middle East Conference on Biomedical engineering (MECBME)

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs).

关键词： Lungs Computed tomography Diseases Active contours Image segmentation Charge carrier processes

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Low power and fast DCT architecture using multiplier-less method

Low power and fast DCT architecture using multiplier-less me...

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Faible Tension Faible Consommation (FTFC)

作者： M. El Aakif S. Belkouch N. Chabini M. M. Hassani Embedded Systems and Digital Control Laboratory National School of Applied Sciences University of Cadi Ayyad Marrakech Morocco Department of Electrical and Computer Engineering Royal Military College of Canada Kingston ONT Canada Faculty of Sciences Semlalia University of Cadi Ayyad Marrakech Morocco

In this paper, a low power and fast DCT (Discrete Cosine Transform) using multiplier-less method is presented with a new modified FGA (Flow-Graph Algorithm), which is derived from our previously presented FGA of DCT based on Loeffler algorithm. The multiplier-less method is based on the replacement of multiplications with a minimum number of additions and shifts. The proposed FGA is performed and compared to a previous one. The results of FPGA implementations on Altera Cyclone II show the increase of the maximum frequency, the decrease of the resources usage and the reduction of the dynamic power by 7.2 % at 120 MHz of clock frequency with a new proposed FGA algorithm. Another comparison with recent published results has been done and proves the efficiency of the proposed FGA.

关键词： Discrete cosine transforms Hardware computer architecture Power demand Field programmable gate arrays Algorithm design and analysis Equations

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Electrocardiogram beat classification using classifier fusion based on Decision Templates

Electrocardiogram beat classification using classifier fusio...

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IEEE International Conference on Cybernetic intelligent systems, CIS

作者： Atena Sajedin Reza Ebrahimpour Tahmoures Younesi Garousi Islamic Azad University Tehran Iran School of Cognitive Sciences(SCS) Institute for Research in Fundamental Sciences Tehran Iran Brain & Intelligent Systems Research Laboratory Department of Electrical and Computer Engineering Shahid Rajaee University Tehran Iran Tolid va maskane khayam Tehran Iran

This paper presents a ”Decision Templates” (DTs) approach to develop customized Electrocardiogram (ECG) beat classifier in an effort to further improve the performance of ECG classification. Taking advantage of the Un-decimated Wavelet Transform (UWT), which also serves as a tool for noise reduction, we extracted 10 ECG morphological, as well as one timing interval features. For classification we have used a number of diverse MLPs neural networks as the base classifiers that are trained by Back Propagation algorithm. Then we employed and compared different combination methods. Tested with MIT/BIH arrhythmia database, we observe significant performance enhancement using this approach.

关键词： Electrocardiography Feature extraction Classification algorithms Databases Training Timing intelligent systems

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures.

关键词： Tumors Anisotropic magnetoresistance Diffusion tensor imaging Support vector machines Feature extraction Artificial neural networks

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