Results 1  10
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171
Matching pursuits with timefrequency dictionaries
 IEEE Transactions on Signal Processing
, 1993
"... AbstractWe introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions. These waveforms are chosen in order to best match the signal structures. Matching pursuits are general procedures t ..."
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Cited by 1671 (13 self)
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matching pursuit isolates the signal structures that are coherent with respect to a given dictionary. An application to pattern extraction from noisy signals is described. We compare a matching pursuit decomposition with a signal expansion over an optimized wavepacket orthonormal basis, selected
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
 California Institute of Technology, Pasadena
, 2008
"... Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery alg ..."
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Cited by 770 (13 self)
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Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery
Selection of Best Orthonormal Rational Basis
, 1997
"... . This contribution deals with the problem of structure determination for generalized orthonormal basis models used in system identification. The model structure is parameterized by a prespecified set of poles. Given this structure and experimental data a model can be estimated using linear regress ..."
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Cited by 5 (1 self)
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. This contribution deals with the problem of structure determination for generalized orthonormal basis models used in system identification. The model structure is parameterized by a prespecified set of poles. Given this structure and experimental data a model can be estimated using linear
Optimal free parameters in orthonormal approximations
 IEEE Trans
, 1998
"... AbstractWe consider orthonormal expansions where the basis functions are governed by some free parameters. If the basis functions adhere to a certain differential or difference equation, then an expression can be given for a specific enforced convergence rate criterion as well as an upper bound fo ..."
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Cited by 4 (0 self)
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AbstractWe consider orthonormal expansions where the basis functions are governed by some free parameters. If the basis functions adhere to a certain differential or difference equation, then an expression can be given for a specific enforced convergence rate criterion as well as an upper bound
On orthonormal Muntz–Laguerre filters
"... When the MüntzSzász condition holds, the MüntzLaguerre filters form a uniformly bounded orthonormal basis in Hardy space. This has consequences in terms of optimal polecancellation schemes, and it also allows for a generalization of Lerch’s theorem. ..."
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Cited by 10 (5 self)
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When the MüntzSzász condition holds, the MüntzLaguerre filters form a uniformly bounded orthonormal basis in Hardy space. This has consequences in terms of optimal polecancellation schemes, and it also allows for a generalization of Lerch’s theorem.
Proximal thresholding algorithm for minimization over orthonormal bases
 SIAM Journal on Optimization
, 2007
"... The notion of soft thresholding plays a central role in problems from various areas of applied mathematics, in which the ideal solution is known to possess a sparse decomposition in some orthonormal basis. Using convexanalytical tools, we extend this notion to that of proximal thresholding and inve ..."
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Cited by 62 (14 self)
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The notion of soft thresholding plays a central role in problems from various areas of applied mathematics, in which the ideal solution is known to possess a sparse decomposition in some orthonormal basis. Using convexanalytical tools, we extend this notion to that of proximal thresholding
An Algorithm For Selection of Best Orthonormal Rational Basis
 in Proc. 36:th IEEE Conf. on Decision and Control
, 1997
"... This contribution deals with the problem of structure determination for generalized orthonormal basis models used in system identification. The model structure is parameterized by a prespecified set of poles. Given this structure and experimental data a model can be estimated using linear regressio ..."
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Cited by 1 (1 self)
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This contribution deals with the problem of structure determination for generalized orthonormal basis models used in system identification. The model structure is parameterized by a prespecified set of poles. Given this structure and experimental data a model can be estimated using linear
SPARSE ORTHONORMAL TRANSFORMS FOR IMAGE COMPRESSION
"... We propose a blockbased transform optimization and associated image compression technique that exploits regularity along directional image singularities. Unlike established work, directionality comes about as a byproduct of the proposed optimization rather than a built in constraint. Our work class ..."
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Cited by 14 (2 self)
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approximation optimized transform coding of images subject to structural constraints on transform basis functions. Index Terms — Sparse orthonormal transforms, sparse lapped transforms, image coding, directional transforms 1.
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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or collimation but by spectral analysis. The idea of Lauterbur (1) to encode object contrast in the resonance spectrum by a magnetic field gradient forms the exclusive basis of signal localization in Fourier imaging. However powerful, the gradientencoding concept implies a fundamental restriction. Only one
ADAPTIVE ORTHONORMAL BASES FOR VIDEO COMPRESSION
"... The paper describes the construction of a vector valued orthonormal basis adapted to an input sequence of video frames. The construction relies on an optimization step that singles out common discontinuities present in the input vector. This is achieved by constructing a sequence of partitions in t ..."
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Cited by 1 (1 self)
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The paper describes the construction of a vector valued orthonormal basis adapted to an input sequence of video frames. The construction relies on an optimization step that singles out common discontinuities present in the input vector. This is achieved by constructing a sequence of partitions
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