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Identifiability and Parameter Estimation of Linear Continuous-time systems under Irregular and Random Sampling

IFAC-PapersOnLine 2015年第28期48卷 332-337页

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Department of Mathematics Wayne State University DetroitMI48202 United States Department of Electrical and Computer Engineering Technology Farmingdale State College State University of New York FarmingdaleNY11735 United States School of Computing Engineering and Mathematics University of Western Sydney PenrithNSW2751 Australia

This paper considers the problem of identifiability and parameter estimation of single-input-single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss-Newton iterative types are developed to generate convergent estimate sequences. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are displayed to verify the theoretical results. © 2015

关键词： Continuous time systems Iterative methods Lyapunov methods Nonlinear control systems Parameter estimation Sampling convergence and asymptotical normality Estimation algorithm Identifiability Irregular sampling Linear continuous time system Non linear least squares

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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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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Comment on 'Inherent security of phase coding quantum key distribution systems against detector blinding attacks' (2018 Laser Phys. Lett. 15 095203)

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Laser Physics Letters 2018年第1期16卷

作者： Aleksey Fedorov Ilja Gerhardt Anqi Huang Jonathan Jogenfors Yury Kurochkin Antía Lamas-Linares Jan-Åke Larsson Gerd Leuchs Lars Lydersen Vadim Makarov Johannes Skaar Russian Quantum Center Skolkovo Moscow 143025 Russia QRate Skolkovo Moscow 143025 Russia QApp Skolkovo Moscow 143025 Russia Institute of Physics University of Stuttgart and Institute for Quantum Science and Technology Pfaffenwaldring 57 D-70569 Stuttgart Germany Max Planck Institute for Solid State Research Heisenbergstraße 1 D-70569 Stuttgart Germany Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People's Republic of China Department of Electrical Engineering Linköping University SE-58183 Linköping Sweden Texas Advanced Computing Center The University of Texas at Austin Austin Texas United States of America Max Planck Institute for the Science of Light and University of Erlangen-Nürnberg D-91058 Erlangen Germany Kringsjåvegen 3E NO-7032 Trondheim Norway National University of Science and Technology MISIS Moscow 119049 Russia Department of Technology Systems University of Oslo Box 70 NO-2027 Kjeller Norway

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Direct and third-body mediated resonance energy transfer in dimensionally constrained nanostructures

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Physical Review B 2015年第3期92卷 035128-035128页

作者： Dilusha Weeraddana Malin Premaratne David L. Andrews []Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia

The process of resonance energy transfer (RET) in a nanostructure influenced by a vicinal, nonabsorbing third body is studied within the framework of molecular quantum electrodynamics. Direct RET and the influence of neighboring matter have been studied previously, mainly for molecules. However, a complete study or unified understanding of direct and indirect RET in nanostructures with different dimensionalities is still lacking. Therefore, there is a strong need for a complete theory that models RET for the cases of quantum wells, nanowires, and quantum dots. We construct a detailed picture of excitation energy transfer in nanostructures and how it is affected by another quantum object, which includes the derivation of quantum amplitudes based on second- and fourth-order time-dependent perturbation theories, and the derivation of transfer rates and distance dependencies, providing a complete picture and understanding of RET in nanostructures. The results of the derivations indicate that the dimensionality of the nanostructure determines the controllability of the RET rate. Furthermore, third-body mediation leads to a nonvanishing RET in the coupling of nanowire to nanowire and quantum dot to quantum dot.

关键词： FLUORESCENCE resonance energy transfer NANOSTRUCTURED materials QUANTUM electrodynamics MOLECULAR structure NANOWIRES ENERGY transfer

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A Distributed Approximation for Multi-Hop Clustering Problem in Wireless Sensor Networks

A Distributed Approximation for Multi-Hop Clustering Problem...

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IEEE Global Communications Conference

作者： Xudong Zhu Jun Li Xiaofeng Gao Fan Wu Guihai Chen Athanasios V. Vasilakos Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Dept of Computer Science Electrical and Space Engineering Lulea University of Technology

ISBN: (纸本)9781479959532

In wireless sensor networks (WSNs), there is no pre-defined infrastructure. Nodes need to frequently flood messages to discover routes, which badly decreases the network performance. To overcome such drawbacks, WSNs are often grouped into several disjointed clusters, each with a representative cluster head (CH) in charge of the routing process. In order to further improve the efficiency of WSNs, it is crucial to find a cluster partition with minimum number of clusters and the distance between each node to its corresponding CH can be bounded by a constant number of hops. Finding such a partition is defined as minimum d-hop cluster head set (d-MCHS) problem, which is proved to be NP-hard. In this paper, we propose a distributed approximation algorithm, named d~2-Cluster, to address d-MCHS problem and prove that the approximation ratio of d~2-Cluster under unit disk graph (UDG) is a constant factor λ which is related to d. To the best of our knowledge, it is the first constant approximation ratio for d-MDS problem in UDG.

关键词： Spread spectrum communication Wireless sensor networks UNG gene Approximation algorithms routing process cluster head approximation Nondeterministic polynomial-time hard hydrated carbon mutual exclusion

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Response Policies to Process Module Failure in Single-Arm Cluster Tools Subject to Wafer Residency Time Constraints

Response Policies to Process Module Failure in Single-Arm Cl...

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作者： Qiao, Yan Pan, Chun-Rong Wu, Nai-Qi Zhou, Mengchu Department of Industrial Engineering School of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou510006 China School of Mechatronics and Electrical Engineering Jiangxi University of Science and Technology Ganzhou341000 China Institute of Systems Engineering Macau University of Science and Technology Taipa China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102-1982 United States

In semiconductor manufacturing, wafer residency time constraints make the scheduling problem of cluster tools complicated. A process module (PM) in cluster tools is prone to failure. It is crucial to deal with any such failure in a proper and timely manner. If there are feasible periodic schedules in operating a cluster tool before and after a PM failure, it is desired to make it operate continuously when such a failure occurs. However, due to wafer residency time constraints, it is highly challenging to control a tool such that it can be correctly transferred from a feasible schedule before failure to another after it. To solve this problem, a Petri net model is developed to describe the dynamic behavior of a single-arm cluster tool and failure response policies are proposed. The proposed policies are formulated via simple control laws for their easy implementation. Examples are given to show them. © 2015 IEEE.

关键词： Scheduling

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Correction to: Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)

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Standards in genomic sciences 2018年第1期13卷 17页

作者： Dagmar Waltemath Frank T Bergmann Claudine Chaouiya Tobias Czauderna Padraig Gleeson Carole Goble Martin Golebiewski Michael Hucka Nick Juty Olga Krebs Nicolas Le Novère Huaiyu Mi Ion I Moraru Chris J Myers David Nickerson Brett G Olivier Nicolas Rodriguez Falk Schreiber Lucian Smith Fengkai Zhang Eric Bonnet 1Department of Systems Biology and Bioinformatics University of Rostock Rostock Germany. 2Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA. 4Instituto Gulbenkian de Ciência - IGC Rua da Quinta Grande Oeiras Portugal. 3IPK Gatersleben Gatersleben Germany. 5Department of Neuroscience Physiology and Pharmacology University College London London UK. 6School of Computer Science The University of Manchester Manchester UK. 7Heidelberg Institute for Theoretical Studies Heidelberg Germany. 8EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton Cambridge UK. 14The Babraham Institute Babraham Research Campus Cambridge UK. 9Department of preventive medicine Keck School of Medicine University of Southern California Los Angeles CA USA. 10Center for Cell Analysis and Modeling University of Connecticut Health Center Farmington CT USA. 11Department of Electrical and Computer Engineering University of Utah Salt Lake City USA. 12Auckland Bioengineering Institute University of Auckland Auckland New Zealand. 13Systems Bioinformatics VU University Amsterdam Amsterdam The Netherlands. 15Martin Luther University Halle-Wittenberg Halle Germany. 16Monash University Melbourne Australia. Computational Biology Unit Laboratory of Systems Biology National Institute of Allergy and Infectious Diseases NIH Bethesda MD USA. 18Institut Curie Paris France. INSERM U900 75248 Paris France. 20Mines ParisTech 77300 Fontainebleau Paris France.

[This corrects the article DOI: 10.4056/sigs.5279417.].

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Hybrid phase-locked loop with fast locking time and low spur in a 0.18-μm CMOS process

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Chinese Physics B 2014年第7期23卷 748-753页

作者：朱思衡司黎明郭超史君宇朱卫仁 Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Department of Electronic Engineering School of Information and ElectronicsBeijing Institute of Technology Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems EngineeringMonash University

We propose a novel hybrid phase-locked loop （PLL） architecture for overcoming the trade-off between fast locking time and low spur. To reduce the settling time and meanwhile suppress the reference spurs, we employ a wide-band single-path PLL and a narrow-band dual-path PLL in a transient state and a steady state, respectively, by changing the loop bandwidth according to the gain of voltage controlled oscillator （VCO） and the resister of the loop filter. The hybrid PLL is implemented in a 0.18-μm complementary metal oxide semiconductor （CMOS） process with a total die area of 1.4×0.46 mm2. The measured results exhibit a reference spur level of lower than -73 dB with a reference frequency of 10 MHz and a settling time of 20 μs with 40 MHz frequency jump at 2 GHz. The total power consumption of the hybrid PLL is less than 27 mW with a supply voltage of 1.8 V.

关键词： phase-locked loop （PLL） fast locking time low spur complementary metal oxide semiconductor（CMOS）

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A decomposition approach to colored traveling salesman problems

A decomposition approach to colored traveling salesman probl...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Jun Li Xing Dai Huaxuan Liu MengChu Zhou Ministry of Education Key Laboratory of Measurement and Control of CSE (Complex Systems of Engineering) Southeast University Nanjing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

As a well-known combinatorial optimization problem, multiple traveling salesman problem (MTSP) fails to characterize some application problems where cities may have different accessibility for some but not necessarily all salesmen. This work proposes a colored traveling salesman problem (CTSP) in which a city has one to multiple colors allowing any salesman with the same color to visit. It presents a decomposition approach that converts CTSP into a combination of several individual traveling salesman problems (TSPs) and one MTSP for an important class of CTSP. To solve the transformed one, this work proposes a modified greedy algorithm allowing multi-colored city assignment during city search and adopts the formerly presented simulated annealing genetic algorithm. A dual-bridge waterjet cutting example is utilized to compare the presented decomposition approach and direct one. The results show that the former can achieve a better solution than the latter if the cities of same color(s) are clumped.

关键词： Cities and towns Color Traveling salesman problems Simulated annealing Genetic algorithms Greedy algorithms

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