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Annual Conference of Industrial Electronics Society

作者： Kiran Kumari Bijnan Bandyopadhyay Abhisek K. Behera Johann Reger Systems and Control Engineering Indian Institute of Technology Bombay Mumbai India Computer Science and Automation Department Technische Universität Ilmenau Ilmenau Germany

The paper presents an event-triggering based sliding mode control law for delta operator systems with disturbance. The discrete domain representation of a system using shift operator becomes numerically ill-conditioned at very high sampling rates. To circumvent this problem, the system is represented using delta operator. The delta operator creates a rapprochement between continuous-time and discrete-time system model at very high sampling rates. A discrete-time sliding mode (DTSM) control law is developed to achieve robustness against external disturbances. Further to reduce the resource utilization, an event-triggered DTSM control law is proposed such that the closed loop system is stable. Due to the inherent discrete nature of the control there is no accumulation of triggering instants at any instant of time. Hence the zeno free execution of the control updating instants is always guaranteed. Simulation results are also shown to illustrate the effectiveness of the proposed method.

关键词： Sliding mode control Trajectory Discrete-time systems Manifolds Numerical models Robustness

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Analysis of Do D inkjet printhead performance for printable electronics fabrication using dynamic lumped element modeling and swarm intelligence based optimal prediction

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Journal of Central South University 2015年第10期22卷 3925-3934页

作者：何茂伟孙丽玲胡琨元朱云龙陈瀚宁 School of Computer Science and Software Tianjin Polytechnic University Department of Information Service & Intelligent Control Shenyang Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences

The major challenge in printable electronics fabrication is to effectively and accurately control a drop-on-demand(Do D) inkjet printhead for high printing quality. In this work, an optimal prediction model, constructed with the lumped element modeling(LEM) and the artificial bee colony(ABC) algorithm, was proposed to efficiently predict the combination of waveform parameters for obtaining the desired droplet properties. For acquiring higher simulation accuracy, a modified dynamic lumped element model(DLEM) was proposed with time-varying equivalent circuits, which can characterize the nonlinear behaviors of piezoelectric printhead. The proposed method was then applied to investigate the influences of various waveform parameters on droplet volume and velocity of nano-silver ink, and to predict the printing quality using nano-silver ink. Experimental results show that, compared with two-dimension manual search, the proposed optimal prediction model perform efficiently and accurately in searching the appropriate combination of waveform parameters for printable electronics fabrication.

关键词： piezoelectric inkjet system lumped element modeling dynamic model nano-silver ink artificial bee colony algorithm

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

arXiv

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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

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An Initial Research:Towards Accurate Pitch Extraction for Speech Synthesis Based on BLSTM

An Initial Research:Towards Accurate Pitch Extraction for Sp...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Yibin Zheng Zhengqi Wen Bin Liu Ya Li Jianhua Tao National Laboratory of Pattern Recognition Institute of AutomationChinese Academy Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy Sciences

Accurate pitch extraction from speech is important but challenging problem for speech synthesis. However, the additive nature and long-term suprasegmental property of pitch features have not been fully exploited in most of the existing pitch estimators as they are operated frame by frame. As a result, they would cause some inherent discontinuities, such as double/half F0 errors and unvoiced/voiced(U/V) error. This would adversely affect the quality of synthetic speech as well as the expressiveness of the prosody information. In this paper, we explore the novel use of multi-tasks(Task 1: U/V;Task 2: Pitch) bidirectional long short-term memory recurrent neural network(BLSTM) to model the pitch and voicing decision simultaneously in a unified framework. The features used in this study are extracted from the frequency domain. We compute the log-frequency power spectrogram and then normalize to the long-term speech spectrum to attenuate noises. A filter is then used to enhance the harmonicity. Experiments show that the proposed approach substantially outperforms RAPT, which behaves the best in clean condition. Besides, our proposed approach can even work well with a certain level of background noise.

关键词： pitch extraction voicing decision BLSTM logfrequency power spectrogram speech synthesis

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LQG control for Networked control Systems in the Presence of Data Packet Drops

LQG Control for Networked Control Systems in the Presence of...

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第35届中国控制会议

作者： Kun Xu Jianming Zhou Fei Liu Guoxiang Gu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University School of Electrical Engineering and Computer Science Louisiana State University

ISBN: (纸本)9781509009107

We study the linear-quadratic-Gaussian(LQG) control for multiple-input/multiple-output(MIMO) discrete-time networked control systems(NCSs) in the presence of data packet drops that are modeled as multiplicative noises,assumed to be white *** will first analyze the mean square(MS) stability problem for MIMO feedback systems in the presence of the multiplicative noises,and provide a new useful MS stability *** LQG control under packet data drops will then be studied in which the critical probability of the received data packet can be computed by solving a set of linear matrices inequalities(LMIs),beyond which the modified algebraic Riccati equations,associated with the LQG control,admit the stabilizing *** a numerical example from the known literature is employed to illustrate our results.

关键词： Networked control system LQG control data packet drop

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Corrigendum: Dielectric cross-shaped-resonator-based metasurface for vortex beam generation at mid-IR and THz wavelengths (Nanophotonics (2019) 8:7 (1263–1270) DOI: 10.1515/nanoph-2019-0112)

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Nanophotonics 2019年

作者： Dharmavarapu, Raghu Izumi, Ken-ichi Katayama, Ikufumi Ng, Soon Hock Vongsvivut, Jitraporn Tobin, Mark J. Kuchmizhak, Aleksandr Nishijima, Yoshiaki Bhattacharya, Shanti Juodkazis, Saulius Centre for NEMS and Nanophotonics (CNNP) Department of Electrical Engineering Indian Institute of Technology Madras Chennai 600036 India Centre for Micro-Photonics Faculty of Science Engineering and Technology Swinburne University of Technology Hawthorn VIC 3122 Australia Melbourne Centre for Nanofabrication ANFF 151 Wellington Road Clayton VIC 3168 Australia Physics Department Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama 240-8501 Japan Infrared Microspectroscopy Beamline Australian Synchrotron Clayton VIC 3168 Australia Institute of Automation and Control Processes Far Eastern Branch Russian Academy of Sciences Vladivostok 690041 Russia Far Eastern Federal University Vladivostok 690090 Russia Department of Electrical and Computer Engineering Graduate School of Engineering Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama 240-8501 Japan Institute of Advanced Sciences Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama 240-8501 Japan Tokyo Tech World Research Hub Initiative (WRHI) School of Materials and Chemical Technology Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo 152-8550 Japan

There was a mistake in the grant number used in the recently published paper (DOI: https://***/10.1515/ nanoph-2019-0112. Published Online: 2019-07-09). The text should read: A.K. is grateful for support via the Russian science Foundation (grant no. 17-19-01325), and R.D. thanks the IIT Madras-Swinburne joint PhD program. © 2019 De Gruyter. All rights reserved.

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Special Issue on Unsupervised Feature Learning for Vision

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IET computer VISION 2015年第5期9卷 627-628页

作者： Zhang, Shengping Zhang, Baochang Ye, Qixiang School of Computer Science and Technology Harbin Institute of Technology Weihai China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing China Institute of Advanced Computer Studies (UMIACS) University of Maryland College Park United States

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Real time Object Tracking based on Local Texture Feature with Correlation Filter

Real time Object Tracking based on Local Texture Feature wit...

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2016 IEEE International Conference on Digital Signal Processing, DSP 2016

作者： Qiao, Meina Wang, Tian Dong, Yuan Shi, Jingang Teng, Jing Snoussi, Hichem School of Automation Science and Electrical Engineering Beihang University Beijing China School of Electronic and Control Engineering Chang'An University Shaanxi Xi'an China School of Electronic and Information Engineering Xi'An JiaotongUniversity Shaanxi Xi'an China School of Control and Computer Engineering North China Electric Power University Beijing China Institute Charles Delaunay-LM2S-UMR STMR 6279 CNRS University of Technology of Troyes France

ISBN: (纸本)9781509041657

Object tracking is a fundamental problem in computer vision, therefore attracts many researchers and there has been many influential algorithms in the list few years. A good feature descriptor is half of the success. In this paper, we propose an effective tracking algorithm based on texture feature with correlation filter. We improve the tracking precision by Haar-like feature and speed it up via discrete Fourier transform. The feature which is a good representation of the target can be obtained via dense sampling. What is more important is that the feature containing a great deal of information of the target appears only in the form of low-dimension. With the property of circluant matrix, we can translate the processes of training and testing into Fourier domain, which can cut the computation and reduce the time complexity. Our algorithm is proved to have better performance especially in deformation and rotation in the benchmark datasets. © 2016 IEEE.

关键词： Discrete Fourier transforms

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Reducing the Modeling Error by Observer Based PID Regulators for a Class of Factorable Nonlinear Plants

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IFAC-PapersOnLine 2015年第11 11期48卷 662-667页

作者： Keviczky, L. Bányász, Cs. Institute of Computer Science and Automation MTA-BME Control Engineering Research Group Hungarian Academy of Sciences H-1111 Budapest Kende u 13-17 Hungary

A PID regulator tuning method is introduced for HAMMERSTEIN and WIENER type block-oriented cascade factorable nonlinear models. Then the YOULA-parameterization approach is discussed which allows to develop an observer... 详细信息

关键词： Proportional control systems Parameterization Hammerstein model Nonlinear process observer PID regulators YOULA regulator

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A new-style decentralized nonlinear robust coordinated control of multiple static synchronous compensators

A new-style decentralized nonlinear robust coordinated contr...

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第35届中国控制会议

作者： Bangjun Lei Xiang Wu Shumin Fei Electrical Engineering College Guizhou Institute of Technology College of Mathmatics and Computer Science Guizhou Normal University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of Automation Southeast University

ISBN: (纸本)9781509009107

Using the pseudo-generalized Hamiltonian method, this paper investigates the decentralized nonlinear robust coordinated control of multiple static synchronous compensators(STATCOMs) in multi-machine multiload power systems. First,the uncertain nonlinear differential algebraic equation model is constructed for the power system. Then, the dissipative pseudogeneralized Hamiltonian realization of the system is established by means of variable transformation and prefeedback ***, based on the obtained dissipative pseudo-generalized Hamiltonian realization, a new-style decentralized nonlinear robust coordinated controller is put forward. Simulation results demonstrate the effectiveness and robustness of the control scheme.

关键词： Pseudo-generalized Hamiltonian function method Uncertain nonlinear differential algebraic system Multimachine power systems Multiple STATCOMs Decentralized nonlinear robust coordinated control

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