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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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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
Sparse coding with an overcomplete basis set: a strategy employed by V1
 Vision Research
, 1997
"... The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive f ..."
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Cited by 958 (9 self)
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field properties may be accounted for in terms of a strategy for producing a sparse distribution of output activity in response to natural images. Here, in addition to describing this work in a more expansive fashion, we examine the neurobiological implications of sparse coding. Of particular interest
On the second eigenvalue and linear expansion of regular graphs.
 In DIMACS Serws in Dncrete Mathematics and Theoretical Computer Science
, 1993
"... Abstract. The spectral method is the best currently known technique to prove lower bounds on expansion. Ramanujan graphs, which have asymptotically optimal second eigenvalue, are the bestknown explicit expanders. The spectral method yielded a lower bound of k\4 on the expansion of Iinearsized sub ..."
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Cited by 16 (2 self)
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sized subsets of kregular Ramanujan graphs. We improve the lower bound ontheexpansion of Ramanujan graphs to approximately k/2, Moreover. we construct afamilyof kregular graphs with asymptotically optimal second eigenvalue and linear expansion equal to k/2. This shows that k/2 is the best bound one can obtain
Stochastic Perturbation Theory
, 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
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Cited by 907 (36 self)
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. In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating
SpatioTemporal Linear Expansions for Repolarization Analysis
"... In this work we propose a multichannel signal model based on linear expansions to analyze the cardiac repolarization. Our hypothesis is that a joint spatiotemporal signal description which takes into account both temporal and spatial features provide a more compact signal representation, i.e. the si ..."
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Cited by 2 (2 self)
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In this work we propose a multichannel signal model based on linear expansions to analyze the cardiac repolarization. Our hypothesis is that a joint spatiotemporal signal description which takes into account both temporal and spatial features provide a more compact signal representation, i
1 APPENDIX C: THE GENERALIZATION OF LINEAR EXPANSION OF RESIDUAL AUTOCORRELATION
, 2007
"... The linear expansion of residual autocorrelations in Box and Pierce (1970) is an approach to deriving the asymptotic distribution of residual autocorrelation functions. Their result was established under the assumption that error sequences have finite variance and the parameters ..."
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The linear expansion of residual autocorrelations in Box and Pierce (1970) is an approach to deriving the asymptotic distribution of residual autocorrelation functions. Their result was established under the assumption that error sequences have finite variance and the parameters
Analysis of Linear Expansivity of Metallic Strips Joined Linearly and with Circular Joints
"... Abstract In this paper the linear expansivity of a metallic strip that are joined linearly and with circular joints were analyzed. The Linear expansivity equations were converted into Integrodifferential equation (IDE) Introduction Metallic strip is used to convert a temperature change into mec ..."
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Abstract In this paper the linear expansivity of a metallic strip that are joined linearly and with circular joints were analyzed. The Linear expansivity equations were converted into Integrodifferential equation (IDE) Introduction Metallic strip is used to convert a temperature change
COMMUNICATIONS in PROBABILITY LINEAR EXPANSION OF ISOTROPIC BROWNIAN FLOWS
"... We consider an isotropic Brownian flow on Rd for d 2 with a positive Lyapunov exponent, and show that any nontrivial connected set almost surely contains points whose distance from the origin under the flow grows linearly with time. The speed is bounded below by a xed constant, which may be compute ..."
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We consider an isotropic Brownian flow on Rd for d 2 with a positive Lyapunov exponent, and show that any nontrivial connected set almost surely contains points whose distance from the origin under the flow grows linearly with time. The speed is bounded below by a xed constant, which may
Approximations of Polytope Enumerators using Linear Expansions
, 2007
"... Several scientific problems are represented as sets of linear (or affine) constraints over a set of variables and symbolic constants. When solutions of interest are integers, the number of such integer solutions is generally a meaningful information. Ehrhart polynomials are functions of the symbol ..."
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Several scientific problems are represented as sets of linear (or affine) constraints over a set of variables and symbolic constants. When solutions of interest are integers, the number of such integer solutions is generally a meaningful information. Ehrhart polynomials are functions
An Iterative Linear Expansion of Thresholds for 1Based Image Restoration
"... Abstract — This paper proposes a novel algorithmic framework to solve image restoration problems under sparsity assumptions. As usual, the reconstructed image is the minimum of an objective functional that consists of a data fidelity term and an 1 regularization. However, instead of estimating the r ..."
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reweighted least square (IRLS), thresholding, linear expansion of thresholds (LET).
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