检索结果-内蒙古大学图书馆

8th IFAC Symposium on Robust control Design, ROCOND 2015

作者： Krishnamurthy, Prashanth Khorrami, Farshad Control/Robotics Research. Laboratory Dept. of ECE NYU Polytechnic School of Engineering BrooklynNY11201 United States

A general class of nonlinear large-scale interconnected systems is considered wherein each subsystem is comprised of a nominal part in a general strict-feedback-like structure and a set of appended dynamics. The system structure is allowed to contain parametric and functional uncertainties, time delays, and a a general coupling interaction structure between dynamic components within each subsystem and across subsystems in the overall large-scale interconnected system. The controller design is based on the dual dynamic high-gain scaling technique and provides decentralized robust adaptive output-feedback delay-independent global stabilization and disturbance attenuation. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Large scale systems

来源：评论

学校读者我要写书评

暂无评论

Detection using optical flow and EMD algorithm and tracking using Kalman filter of moving Objects

引用

Transactions of the Korean Institute of Electrical Engineers 2015年第7期64卷 1047-1055页

作者： Lee, Jung Sik Joo, Yung Hoon Dept. of Control and Robotics Engineering Kunsan National University Korea Republic of

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments. Copyright © The Korean Institute of Electrical Engineers.

关键词： Optical flows

来源：评论

学校读者我要写书评

暂无评论

Visual touch recognition for NUI using Voronoi-tessellation algorithm

引用

Transactions of the Korean Institute of Electrical Engineers 2015年第3期64卷 465-472页

作者： Kim, Sung Kwan Joo, Young Hoon Dept. of Control and Robotics Engineering Kunsan National University Korea Republic of Dept. of Control and Robot Engineering Kunsan National University Korea Republic of

This paper presents a visual touch recognition for NUKNatural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments. Copyright © The Korean Institute of Electrical Engineers.

关键词： User interfaces

来源：评论

学校读者我要写书评

暂无评论

Decentralized Output-Feedback for Delayed Large-Scale Interconnected Nonlinear Systems via Dynamic High-Gain Scaling

引用

IFAC-PapersOnLine 2015年第14期48卷 247-252页

作者： Prashanth Krishnamurthy Farshad Khorrami Control/Robotics Research Laboratory Dept. of ECE NYU Polytechnic School of Engineering Brooklyn NY 11201 USA

关键词：

来源：评论

学校读者我要写书评

暂无评论

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wrocla...

引用

12th Workshop on Stochastic Models, Statistics and their Applications, 2015

作者： Steland, Ansgar Szajowski, Krzysztof Rafajlowicz, Ewaryst Institute of Statistics RWTH Aachen University Aachen Germany Inst. of Mathematics and Computer Science Wroclaw University of Technology Wroclaw Poland Dept. of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

来源：评论

学校读者我要写书评

暂无评论

Multiple-Dynamic-Scaling Output-Feedback control for Uncertain Strict-Feedback-Like Systems with Input Unmodeled Dynamics

Multiple-Dynamic-Scaling Output-Feedback Control for Uncerta...

引用

American control Conference

作者： P. Krishnamurthy F. Khorrami Control/Robotics Research Laboratory (CRRL) Dept. of ECE NYU Polytechnic School of Engineering Brooklyn NY 11201 USA

ISBN: (纸本)9781479917730

A general class of uncertain strict-feedback-like nonlinear systems with dynamic input nonlinearities is considered. The addressed nonlinear system structure can be viewed as a nominal system of strict-feedback-like form with its input signal given by an uncertain nonlinear function coupled with an uncertain nonlinear time-varying input unmodeled dynamics. The proposed controller is based on a scaling-based redesign of the dual dynamic high-gain scaling based output-feedback control design for strict-feedback-like systems. The scaling-based redesign introduces a dynamic state extension and an additional dynamic scaling based on a singular-perturbation-like structure to address the nonlinear uncertain dynamic input perturbation. The proposed approach provides a globally stabilizing output-feedback control design that is robust to the uncertain input unmodeled dynamics and functional and parameteric uncertainties allowed in the system structure.

关键词： Nonlinear dynamical systems control design Observers Uncertainty Lyapunov methods Closed loop systems

来源：评论

学校读者我要写书评

暂无评论

Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

引用

arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

Selection of 5 kW converter leg for power electronic system for residential buildings

Selection of 5 kW converter leg for power electronic system ...

引用

European Conference on Power Electronics and Applications

作者： Marcin Zygmanowski Jaroslaw Michalak Michal Jelen Grzegorz Jarek Jan Popczyk Faculty of Electrical Engineering Dept. of Power Electronics Electrical Drives and Robotics SILESIAN UNIVERSITY OF TECHNOLOGY ul. B. Krzywoustego 2 Gliwice Poland Faculty of Electrical Engineering Institute of Power Systems and Control SILESIAN UNIVERSITY OF TECHNOLOGY ul. B. Krzywoustego 2 Gliwice Poland

ISBN: (纸本)9781509014101

Three converter leg variants are analyzed for low power converter used for power electronic system for residential buildings. The two-level Si-IGBT and SiC-MOSFET converters are compared with Si-IGBT three-level T-type converter. Power losses generated in each of these converters over a predicted period of 20 years of operation are contrasted with the cost of converter options. The detailed selection procedure for output inductor is presented in this paper. This procedure shows the influence of the inductor parameters like number of turns, air gap length on its losses, cost and size. Theoretical approach is verified with simulations and experimental results.

关键词： Design IGBT Silicon Carbide (SiC) MOSFET Microgrid

来源：评论

学校读者我要写书评

暂无评论

Frequency Domain Analysis of HOSM Systems

Frequency Domain Analysis of HOSM Systems

引用

IEEE Annual Conference on Decision and control

作者： Antonio Rosales Yuri Shtessel Leonid Fridman Chandrasekhara Bharath Panathula Electrical and Computer Engineering Dept. The University of Alabama in Huntsville Huntsville AL 35899 USA Deparment of Control and Robotics Faculty of Engineering National Autonomus University of Mexico 4510 Mexico City Mexico

ISBN: (纸本)9781479978878

The frequency domain analysis of dynamically perturbed Higher Order Sliding Mode (HOSM) systems is tackled using Describing Function (DF) and Harmonic Balance (HB) techniques. The goal of this analysis is to study possible limit cycles in such systems. DFs of Nested 3rd and 4th order algorithms are obtained for the first time. Then, HB equation is used to analyze the real sliding motion in the HOSM system, where the sliding set converges to a limit cycle. Chattering (limit cycle) in the HOSM systems is studied, and the chattering parameters (amplitude and frequency) are computed. A definition of Tolerance Limits, which characterizes the acceptable performance in the real HOSM system, is applied to verify if the chattering parameters fit the amplitude and frequency limits. Next, Performance Phase Margin and Performance Gain Margin definitions, which give the metrics for robustness of real HOSM to unmodeled dynamics, are applied to assess the robustness of the limit cycle emerged in the real HOSM system. Examples and simulations that validate the obtained results are presented.

关键词： Sliding Mode control Frequency Domain Analysis Performance Margins Variable structure systems limit cycles CHATTER unmodeled dynamics

来源：评论

学校读者我要写书评

暂无评论

Improved Drive Cycle Following with an ILC Supported Driver Model ∗

引用

IFAC-PapersOnLine 2015年第15期48卷 347-353页

作者： Lars Eriksson Mikael Norrlöf Lars Eriksson is with Vehicular Systems Dept. of Electrical Engineering Linköping University SE-581 83 Linköping Sweden Mikael Norrlöf is with Automatic Control Dept. of Electrical Engineering Linköping University SE-581 83 Linköping Sweden and ABB AB - Robotics SE-721 68 Västerås Sweden

Drive cycle following is important for concept comparisons when evaluating vehicle concepts, but it can be time consuming to develop good driver models that can achieve accurate following of a specific velocity profile. Here, a new approach is proposed where a simple driver model based on a PID controller is extended with an Iterative Learning control (ILC) algorithm. Simulation results using a nonlinear vehicle and control system model show that it is possible to achieve very good cycle following in a few iterations with little tuning effort. It is also possible to utilize the repetitive behavior in the drive cycle to accelerate the convergence of the ILC algorithm even further.

关键词： Vehicle control learning powertrain

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：