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Compressed Sensing Off the Grid
, 2012
"... This work investigates the problem of estimating the frequency components of a mixture of s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous work in compressed sensing, the frequencies are not assumed to lie on a grid, but can assume any values in the normalized ..."
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Cited by 25 (1 self)
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This work investigates the problem of estimating the frequency components of a mixture of s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous work in compressed sensing, the frequencies are not assumed to lie on a grid, but can assume any values in the normalized
Compressed Sensing Off the Grid
, 2012
"... This work investigates the problem of estimating the frequency components of a mixture of s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous work in compressed sensing, the frequencies are not assumed to lie on a grid, but can assume any values in the normalized ..."
Abstract
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This work investigates the problem of estimating the frequency components of a mixture of s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous work in compressed sensing, the frequencies are not assumed to lie on a grid, but can assume any values in the normalized
LU et al.: DISTRIBUTED COMPRESSED SENSING OFF THE GRID 1 Distributed Compressed Sensing off the Grid
"... Abstract—This letter investigates the joint recovery of a frequencysparse signal ensemble sharing a common frequencysparse component from the collection of their compressed measurements. Unlike conventional arts in compressed sensing, the frequencies follow an offthegrid formulation and are con ..."
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Abstract—This letter investigates the joint recovery of a frequencysparse signal ensemble sharing a common frequencysparse component from the collection of their compressed measurements. Unlike conventional arts in compressed sensing, the frequencies follow an offthegrid formulation
Compressive sampling
, 2006
"... Conventional wisdom and common practice in acquisition and reconstruction of images from frequency data follow the basic principle of the Nyquist density sampling theory. This principle states that to reconstruct an image, the number of Fourier samples we need to acquire must match the desired res ..."
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Cited by 1427 (15 self)
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resolution of the image, i.e. the number of pixels in the image. This paper surveys an emerging theory which goes by the name of “compressive sampling” or “compressed sensing,” and which says that this conventional wisdom is inaccurate. Perhaps surprisingly, it is possible to reconstruct images or signals
Complete discrete 2D Gabor transforms by neural networks for image analysis and compression
, 1988
"... AbstractA threelayered neural network is described for transforming twodimensional discrete signals into generalized nonorthogonal 2D “Gabor ” representations for image analysis, segmentation, and compression. These transforms are conjoint spatiahpectral representations [lo], [15], which provide ..."
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Cited by 475 (8 self)
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AbstractA threelayered neural network is described for transforming twodimensional discrete signals into generalized nonorthogonal 2D “Gabor ” representations for image analysis, segmentation, and compression. These transforms are conjoint spatiahpectral representations [lo], [15], which
Qualitative Researching
, 1996
"... ltaic (PV) electricity production from an intermittent Since 1978, compressed air energy storage (CAES) compressed air can then be released on demand to the CAES plant’s turbogenerator set to generate premium value electricity. The first CAES plant was built in broadened in the ittency of wind g wi ..."
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Cited by 591 (0 self)
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ltaic (PV) electricity production from an intermittent Since 1978, compressed air energy storage (CAES) compressed air can then be released on demand to the CAES plant’s turbogenerator set to generate premium value electricity. The first CAES plant was built in broadened in the ittency of wind g
Using spin images for efficient object recognition in cluttered 3D scenes
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1999
"... We present a 3D shapebased object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the spinimage representation. The spinimage is a data level shape descriptor that i ..."
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Cited by 571 (9 self)
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that is used to match surfaces represented as surface meshes. We present a compression scheme for spinimages that results in efficient multiple object recognition which we verify with results showing the simultaneous recognition of multiple objects from a library of 20 models. Furthermore, we demonstrate
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
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Cited by 1513 (20 self)
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measurements do we need to recover objects from this class to within accuracy ɛ? This paper shows that if the objects of interest are sparse or compressible in the sense that the reordered entries of a signal f ∈ F decay like a powerlaw (or if the coefficient sequence of f in a fixed basis decays like a power
2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late Nineteenth Century
 J. Geophysical Research
"... data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitudelongitude grid ..."
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Cited by 517 (3 self)
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data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitudelongitude grid
Distributed Computing in Practice: The Condor Experience
 Concurrency and Computation: Practice and Experience
, 2005
"... Since 1984, the Condor project has enabled ordinary users to do extraordinary computing. Today, the project continues to explore the social and technical problems of cooperative computing on scales ranging from the desktop to the worldwide computational grid. In this chapter, we provide the history ..."
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Cited by 542 (7 self)
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Since 1984, the Condor project has enabled ordinary users to do extraordinary computing. Today, the project continues to explore the social and technical problems of cooperative computing on scales ranging from the desktop to the worldwide computational grid. In this chapter, we provide
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