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检索条件"机构=Applied Mathematics and Computational Science Program Computer"
489 条 记 录,以下是421-430 订阅
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Reducing time delays on congested road networks using social navigation
Reducing time delays on congested road networks using social...
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IEEE Forum on Integrated and Sustainable Transportation System (FISTS)
作者: Alje van den Bosch Bart van Arem Mohamed Mahmod James Misener Department of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Partners for Advanced Transit and Highways (PATH) program University of California Berkeley USA Department of Transport and Planning at the Faculty of Civil Engineering and Geosciences Delft University of Technnology Netherlands Centre of Transport Studies Faculty of Engineering University of Twente Enschede Netherlands
Social navigation provides drivers with an advice that aims to shift traffic flows in a network from a user equilibrium to a system optimum. The advice is based on minimizing a combination of the individual travel tim... 详细信息
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Recovery of frequency-sparse signals from compressive measurements
Recovery of frequency-sparse signals from compressive measur...
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48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
作者: Duarte, Marco F. Baraniuk, Richard G. Program in Applied and Computational Mathematics Princeton University United States Department of Electrical and Computer Engineering Rice University United States
Compressive sensing (CS) is a new approach to simultaneous sensing and compression for sparse and compressible signals. While the discrete Fourier transform has been widely used for CS of frequency-sparse signals, it ... 详细信息
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Hierarchical clustering via localized diffusion folders
Hierarchical clustering via localized diffusion folders
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2010 AAAI Fall Symposium
作者: David, Gil Averbuch, Amir Coifman, Ronald R. Department of Mathematics Program in Applied Mathematics Yale University United States School of Computer Science Tel-Aviv University Israel
We present a short introduction to an hierarchical clustering method of high-dimensional data via localized diffusion folders. Copyright © 2010, Association for the Advancement of Artificial Intelligence. All rig... 详细信息
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Why Gabor frames? Two fundamental measures of coherence and their role in model selection
Why Gabor frames? Two fundamental measures of coherence and ...
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作者: Bajwa, Waheed U. Calderbank, Robert Jafarpour, Sina Department of Electrical Engineering Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 United States Department of Computer Science Princeton University Princeton NJ 08544 United States
The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model... 详细信息
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K, T and D-like fuzzy Kripke models
K, T and D-like fuzzy Kripke models
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Conference of the North American Fuzzy Information Processing Society - NAFIPS
作者: Benjamin Bedregal Regivan H. N. Santiago Mario Benevides Petrúcio Viana Group of Logic Language Information Theory and Applications-LoLITA Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Program of Engineering of Systems and Computing-PESC Department of Computer Science Federal University of Rio de Janeiro Rio de Janeiro Rio de Janeiro Brazil Department of Analysis Fluminense Federal University (UFF) Niteroi Rio de Janeiro Brazil
The idea of a Kripke semantics endowed with possibility/plausibility information is not new; in fact there are different approaches for that; see: [6], [13], [16], [19]. This paper follows the approach found in [6], b... 详细信息
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Combining wireless neural recording and video capture for the analysis of natural gait
Combining wireless neural recording and video capture for th...
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International IEEE/EMBS Conference on Neural Engineering, CNE
作者: Justin D. Foster Oren Freifeld Paul Nuyujukian Stephen I. Ryu Michael J. Black Krishna V. Shenoy Department of Electrical Engineering University of Stanford Stanford CA USA Division of Applied Mathematics Brown University Providence RI USA Bioengineering and Stanford Medical School University of Stanford Stanford CA USA Department of Neurosurgery Palo Alto Medical Foundation Palo Alto CA USA Department of Computer Science Brown University Providence RI USA Max-Planck Institute Tubingen Germany Departments of Electrical Engineering Bioengineering and Neurobiology and the Neurosciences Program University of Stanford Stanford CA USA
Neural control of movement is typically studied in constrained environments where there is a reduced set of possible behaviors. This constraint may unintentionally limit the applicability of findings to the generalize... 详细信息
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High-dimensional data fusion via joint manifold learning
High-dimensional data fusion via joint manifold learning
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2010 AAAI Fall Symposium
作者: Davenport, Mark A. Hegde, Chinmay Duarte, Marco F. Baraniuk, Richard G. Department of Statistics Stanford University Stanford CA 94305 United States Department of Electrical and Computer Engineering Rice University Houston TX 77005 United States Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 United States
The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that acquire large amounts of very high-dimensional data. To cope with such a data deluge, manifold... 详细信息
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TEXAS HOLD'EM ALGORITHMS FOR DISTRIBUTED COMPRESSIVE SENSING
TEXAS HOLD'EM ALGORITHMS FOR DISTRIBUTED COMPRESSIVE SENSING
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IEEE International Conference on Acoustics, Speech, and Signal Processing
作者: Stephen R. Schnelle Jason N. Laska Chinmay Hegde Marco F. Duarte Mark A. Davenport Richard G. Baraniuk Department of Electrical and Computer Engineering Rice University Houston TX 77005 Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544
This paper develops a new class of algorithms for signal recovery in the distributed compressive sensing (DCS) framework. DCS exploits both intra-signal and inter-signal correlations through the concept of joint spars... 详细信息
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KRONECKER PRODUCT MATRICES FOR COMPRESSIVE SENSING
KRONECKER PRODUCT MATRICES FOR COMPRESSIVE SENSING
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IEEE International Conference on Acoustics, Speech, and Signal Processing
作者: Marco F. Duarte Richard G. Baraniuk Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 Department of Electrical and Computer Engineering Rice University Houston TX 77005
Compressive sensing (CS) is an emerging approach for acquisition of signals having a sparse or compressible representation in some basis. While CS literature has mostly focused on problems involving 1-D and 2-D signal... 详细信息
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USING REED-MULLER SEQUENCES AS DETERMINISTIC COMPRESSED SENSING MATRICES FOR IMAGE RECONSTRUCTION
USING REED-MULLER SEQUENCES AS DETERMINISTIC COMPRESSED SENS...
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IEEE International Conference on Acoustics, Speech, and Signal Processing
作者: Kangyu Ni Somantika Datta Prasun Mahanti Svetlana Roudenko Douglas Cochran School of Mathematical and Statistical Sciences Arizona State University Program in Applied and Computational Mathematics Princeton University School of Electrical Computer and Energy Engineering Arizona State University
An image reconstruction algorithm using compressed sensing (CS) with deterministic matrices of second-order Reed-Muller (RM) sequences is introduced. The 1D algorithm of Howard et al. using CS with RM sequences suffer... 详细信息
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