Results 361 to 370 of about 11,243,181 (388)
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A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal of Imaging Sciences, 2009We consider the class of iterative shrinkage-thresholding algorithms (ISTA) for solving linear inverse problems arising in signal/image processing.
Amir Beck, M. Teboulle
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$rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing, 2006In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms.
M. Aharon, Michael Elad, A. Bruckstein
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Concept of an Algorithm. Correctness of Algorithms
2018Algorithm is an exact prescription determining the computation process, leading from the varying source data to the sough result (data is the ordered set of characters). In other words, an algorithm describes the certain computation procedure, with the help of which the computation problem is solved.
Sergei Borzunov, Sergei Kurgalin
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ACM SIGPLAN Lisp Pointers, 1991
It is my intention to publish two different kinds of algorithms articles: articles that present utilities built on top of Common Lisp and articles that discuss and explain interesting parts of Common Lisp. The following article is an example of the latter type.
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It is my intention to publish two different kinds of algorithms articles: articles that present utilities built on top of Common Lisp and articles that discuss and explain interesting parts of Common Lisp. The following article is an example of the latter type.
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A non-local algorithm for image denoising
Computer Vision and Pattern Recognition, 2005We propose a new measure, the method noise, to evaluate and compare the performance of digital image denoising methods. We first compute and analyze this method noise for a wide class of denoising algorithms, namely the local smoothing filters.
A. Buades, B. Coll, J. Morel
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, 2011 The Expectation-Maximization (EM) algorithm is a broadly applicable approach to the iterative computation of maximum likelihood estimates in a wide variety of incomplete-data problems. The EM algorithm has a number of desirable properties, such as its numerical stability, reliable global convergence, and simplicity of implementation. There are, however,
Ng, S. K. +2 more
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Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory, 2001Algorithms that must deal with complicated global functions of many variables often exploit the manner in which the given functions factor as a product of "local" functions, each of which depends on a subset of the variables.
F. Kschischang +2 more
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Algorithms Creating Algorithms
2010The spontaneous synthesis of algorithms in artificial neural networks is experimented and analyzed on three hierarchical levels and there are three basic problems: How the engram of memory connects the neuron state and the combination of messages from other neurons. How the cortical column decodes the parallel series of impulses from other columns. How
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The College Mathematics Journal, 1987
(1987). Algorithm of The Bi_Month. The College Mathematics Journal: Vol. 18, No. 2, pp. 153-156.
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(1987). Algorithm of The Bi_Month. The College Mathematics Journal: Vol. 18, No. 2, pp. 153-156.
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Development and validation of a genetic algorithm for flexible docking.
Journal of Molecular Biology, 1997Prediction of small molecule binding modes to macromolecules of known three-dimensional structure is a problem of paramount importance in rational drug design (the "docking" problem).
G. Jones +4 more
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