Results 151 to 160 of about 206,616 (184)

Oblique Projection Matching Pursuit

Mobile Networks and Applications, 2016
Recent theory of compressed sensing (CS) tells us that sparse signals can be reconstructed from a small number of random samples. In reconstruction of sparse signals, greedy algorithms, such as the orthogonal matching pursuit (OMP), have been shown to be computationally efficient.
Jian Wang, Feng Wang, Yunquan Dong, Byonghyo Shim   +3 more
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Refining Kernel Matching Pursuit

2010
Kernel matching pursuit (KMP), as a greedy machine learning algorithm, appends iteratively functions from a kernel-based dictionary to its solution An obvious problem is that all kernel functions in dictionary will keep unchanged during the whole process of appending It is difficult, however, to determine the optimal dictionary of kernel functions ...
Jianwu Li, Yao Lu
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Matching pursuit filter design

Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), 2002
A method has been devised of using localized information to detect objects with varying signatures without prior segmentation. The detection is performed by a new class of nonlinear filters called matching pursuit filters, which are trained on multiple examples of the object of interest. Matching pursuit filters are designed through a generalization of
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Covariance-Assisted Matching Pursuit

IEEE Signal Processing Letters, 2016
We consider the problem of greedy sparse approximation in the presence of noise, given a-priori knowledge of the sparse coefficients’ covariance and mean. The proposed Covariance-Assisted Matching Pursuit (CAMP) combines the a-priori knowledge by leveraging the Gauss-Markov theorem, and provides significantly better performance than the classical ...
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Improved Matching Pursuits Image Coding

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
This paper reports improvements in compression of both inter- and intra-frame images by the matching pursuits (MP) algorithm. For both types of image, applying a 2D wavelet decomposition prior to MP coding is beneficial. The MP algorithm is then applied using various separable ID codebooks. MERGE coding with precision limited quantization (PLQ) is used
null Yuan Yuan, D.M. Monro
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Online search Orthogonal Matching Pursuit

2012 IEEE Statistical Signal Processing Workshop (SSP), 2012
The recovery of a sparse signal x from y= Φx, where Φ is a matrix with more columns than rows, is a task central to many signal processing problems. In this paper we present a new greedy algorithm to solve this type of problem. Our approach leverages ideas from the field of online search on state spaces.
Alejandro J. Weinstein, Michael B. Wakin
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Orthogonal Matching Pursuit with correction

2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA), 2016
Orthogonal Matching Pursuit (OMP) is the most popular greedy algorithm that has been developed to find a sparse solution vector to an under-determined linear system of equations. OMP follows the projection procedure to identify the indices of the support of the sparse solution vector.
Nasser Mourad, Maha Sharkas, Mostafa M. Elsherbeny   +2 more
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Probabilistic Orthogonal Matching Pursuit

2022 IEEE International Conference on Big Data (Big Data), 2022
Ghazal Fazelnia, John Paisley
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The design of matching pursuit filters

Network: Computation in Neural Systems, 1998
This paper presents a new technique for creating efficient and compact models from data, called matching pursuit filters. The design of a matching pursuit filter is based on an adapted wavelet expansion, where the expansion is adapted to both the data and the pattern recognition problem being addressed.
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Matching pursuit with damped sinusoids

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
The matching pursuit algorithm derives an expansion of a signal in terms of the elements of a large dictionary of time-frequency atoms. This paper considers the use of matching pursuit for computing signal expansions in terms of damped sinusoids. First, expansion based on complex damped sinusoids is explored; it is shown that the expansion can be ...
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