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International Conference on ASIC

作者： Lian Huai Samer Hijazi Raul Casas Gerald E. Sobelman Department of Electrical and Computer Engineering University of Minnesota Minneapolis USA Cadence Design Systems San Jose USA

This paper presents a novel low-complexity, hard output multiple-input, multiple-output (MIMO) detection algorithm and architecture for LTE and WiFi applications. Our method provides a well-defined tradeoff between computational complexity and performance. The proposed algorithm does not require QR decomposition as a preprocessing step, as is commonly needed in sphere detection (SD). Simulation results for 3×3 and 4×4 MIMO configurations with both 16 and 64 QAM constellations show that the proposed algorithm uses a much smaller number of Euclidean distance (ED) calculations than other methods while having only a 0.5 dB loss compared to maximum likelihood detection. A 3×3 MIMO system with a 16 QAM detector architecture is also described, and the associated latency and hardware costs are given.

关键词： MIMO Quadrature amplitude modulation Complexity theory Signal to noise ratio computer architecture Detectors Algorithm design and analysis

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IRRADIATION OF ON-CHIP CHALCOGENIDE GLASS WAVEGUIDE MID-INFRARED GAS SENSOR

IRRADIATION OF ON-CHIP CHALCOGENIDE GLASS WAVEGUIDE MID-INFR...

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IEEE Sensors

作者： Peter Su Zhaohong Han Derek Kita Vivek Singh Qingyang Du Lionel Kimerling Juejun Hu Anu Agarwal Pao Tai Lin Kathleen Richardson Dawn T. H. Tan Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge Massachusetts USA Electrical and Computer Engineering College Station Texas USA CREOL University of Central Florida Orlando Florida USA Photonics Devices and Systems Group Singapore University of Technology and Design Singapore Singapore

We measure the effect of radiation damage on an on-chip mid-infrared methane gas sensor made using a spiral chalcogenide glass waveguide. The sensor is fabricated using UV lithography and a lift-off process after deposition of chalcogenide glass using a thermal evaporator. We measure the transmittance change of the sensor at varying concentrations of methane after varying doses of irradiation.

关键词： radiation gas detection gas sensor chalcogenide glass integrated photonics

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Editorial

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Technometrics 2015年第3期57卷 303-304页

作者： Yong Chen[a] V. Roshan Joseph[c] Yu Ding[b] Vijay Nair[d] [a] Department of Mechanical and Industrial Engineering University of Iowa Iowa City IA 52242 ()[b] Departments of Industrial & Systems Engineering and Electrical & Computer Engineering Texas A&M University College Station TX 77843 ()[c] Stewart School of Industrial & Systems Engineering Georgia Institute of Technology Altlanta GA 30332 ()[d] Departments of Statistics and Industrial & Operations Engineering The University of Michigan Ann Arbor MI 48109 ()

"Editorial."Technometrics, 57(3), pp. 303–304

关键词： Ordinary differential equations Wind turbines

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Power-efficient algorithms for autonomous navigation

Power-efficient algorithms for autonomous navigation

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International Conference on Complex systems engineering (ICCSE)

作者： Yash Vardhan Pant Houssam Abbas K. N. Nischal Paritosh Kelkar Dhruva Kumar Joseph Devietti Rahul Mangharam The Departments of Electrical and Systems Engineering and Computer and Information Sciences University of Pennsylvania Philadelphia U.S.A. University of Pennsylvania Philadelphia PA US

Real-time navigation of autonomous vehicles requires the processing of a large amount of sensor data by the perception algorithms onboard the vehicle, like object detection and localization. To meet the driving performance and safety requirements, these algorithms require the hardware to be over-engineered to always operate for the worst-case. This leads to excessive power consumption by the computation platform. In this paper, we study how platform-level optimizations affect the computation throughput and power, and how to use this trade-off to save computation power without overly degrading throughput and control performance. The approach uses an offline profiling stage of the perception algorithm, which gives us Throughput versus Power curves for various processor frequencies and various scheduling of the perception code on CPU and GPU. At runtime, we combine power and throughput into one objective function, and design a supervisor what will determine the frequency and CPU/GPU allocation to maximize the objective. We illustrate our approach on a scaled-down autonomous car which uses Vanishing Point navigation. Experimental results demonstrate that we can achieve an energy savings of upto 20% while degrading control performance by less than 1%.

关键词： Throughput Graphics processing units Navigation Schedules Power demand Delays Algorithm design and analysis

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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High power factor single stage flyback converter for dimmable LED driver 7

High power factor single stage flyback converter for dimmabl...

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7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015

作者： Jia, Liang Liu, Yan-Fei Fang, David Department of Electrical and Computer Engineering Queen's University KingstonONK7L 3N6 Canada LED Systems Global Design Center Philips Electronics North America 10275 W. Higgins Rd RosemontIL60018 United States

Single stage Flyback converter with active power factor correction (PFC) function built-in is very popular for low power LED driver application. However, a universal driver design (120V∼277Vac wide input) for meeting... 详细信息

ISBN: (纸本)9781467371506

关键词： Light emitting diodes

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Multiscale dictionary learning: non-asymptotic bounds and robustness

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Mauro Maggioni Stanislav Minsker Nate Strawn Google MPI for Intelligent Systems Departments of Mathematics Electrical and Computer Engineering and Computer Science Duke University Durham NC Department of Mathematics University of Southern California Los Angeles CA Department of Mathematics and Statistics Georgetown University Washington D.C.

High-dimensional datasets are well-approximated by low-dimensional structures. Over the past decade, this empirical observation motivated the investigation of detection, measurement, and modeling techniques to exploit these low-dimensional intrinsic structures, yielding numerous implications for high-dimensional statistics, machine learning, and signal processing. Manifold learning (where the low-dimensional structure is a manifold) and dictionary learning (where the low-dimensional structure is the set of sparse linear combinations of vectors from a finite dictionary) are two prominent theoretical and computational frameworks in this area. Despite their ostensible distinction, the recently-introduced Geometric Multi-Resolution Analysis (GMRA) provides a robust, computationally efficient, multiscale procedure for simultaneously learning manifolds and *** this work, we prove non-asymptotic probabilistic bounds on the approximation error of GMRA for a rich class of data-generating statistical models that includes "noisy" manifolds, thereby establishing the theoretical robustness of the procedure and confirming empirical observations. In particular, if a dataset aggregates near a low-dimensional manifold, our results show that the approximation error of the GMRA is completely independent of the ambient dimension. Our work therefore establishes GMRA as a provably fast algorithm for dictionary learning with approximation and sparsity guarantees. We include several numerical experiments confirming these theoretical results, and our theoretical framework provides new tools for assessing the behavior of manifold learning and dictionary learning procedures on a large class of interesting models.

关键词： dictionary learning manifold learning multi-resolution analysis robustness sparsity

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Classifier fusion interactive software toolbox for EMG signal decomposition

Classifier fusion interactive software toolbox for EMG signa...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： Sarbast Rasheed Daniel W. Stashuk Mohamed S. Kamel Department of Engineering The American University of Iraq Sulaimani Iraq Department of Systems Design Engineering University of Waterloo Waterloo Ontario Canada M. S. Kamel is with the Department of Electrical and Computer Engineering University of Waterloo Waterloo Ontario Canada

ISBN: (纸本)9781479958306

A classifier fusion interactive software package has been constructed for implementing the classification task in the electromyographic (EMG) signal decomposition process using the MATLAB high-level programming language and its interactive environment. The package employs classifier fusion schemes of multiple classifier combination for the purpose of fusing the decisions of a set of heterogeneous base classifiers to make a final decision that achieves improved classification performance. The base classifiers used are ensembles of error-independent certainty, fuzzy k-NN, and template matched filter classifiers. The interactive package consists of several graphical user interfaces (GUIs) to extract individual motor unit potential (MUP) waveforms from raw EMG signals; extract relevant features; classify MUPs into motor unit potential trains (MUPTs) using certainty-based, assertion-based, and similarity-based classifiers; and combine classifier decisions. The proposed software package is useful for enhancing the EMG signal analysis quality and providing a systematic approach to the EMG signal decomposition process. It worked as a very helpful environment for testing and evaluating algorithms developed for EMG signal decomposition research.

关键词： Electromyography Signal resolution Feature extraction computers Software packages Accuracy Pattern recognition

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Computational advancement in communication circuits and systems: Proceedings of ICCACCS 2014 1

Computational advancement in communication circuits and syst...

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1st International Conference on Computational Advancement in Communication Circuits and systems, ICCACCS 2014

作者： Maharatna, Koushik Dalapati, Goutam Kumar Banerjee, P.K. Mallick, Amiya Kumar Mukherjee, Moumita School of Electronics and Computer Science University of Southampton Southampton United Kingdom Department of Design and Growth Institute of Materials Research and Engineering Singapore Singapore Electronics and Telecommunication Engineering Jadavpur University Kolkata West Bengal India Electronics and Electrical Communication Indian Institute of Technology Kharagpur Kharagpur West Bengal India Centre for Millimeter Wave Semiconductor Devices and Systems Defence Research and Development Organisation Kolkata West Bengal India

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