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Image denoising using a scale mixture of Gaussians in the wavelet domain
 IEEE TRANS IMAGE PROCESSING
, 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
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Cited by 513 (17 self)
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We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian
Junctional complexes in various epithelia
 J. CELL BIOL
, 1963
"... The epithelia of a number of glands and cavitary organs of the rat and guinea pig have been surveyed, and in all cases investigated, a characteristic tripartite junctional complex has been found between adjacent cells. Although the complex differs in precise arrangement from one organ to another, it ..."
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Cited by 265 (4 self)
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basal direction. The zonula occludens (tight junction) is characterized by fusion of the adjacent cell membranes resulting in obliteration of the intercellular space over variable distances. Within the obliterated zone, the dense outer leaflets of the adjoining cell membranes converge to
How Good is Local Type Inference?
, 1999
"... A partial type inference technique should come with a simple and precise specification, so that users predict its behavior and understand the error messages it produces. Local type inference techniques attain this simplicity by inferring missing type information only from the types of adjacent synta ..."
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Cited by 185 (4 self)
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A partial type inference technique should come with a simple and precise specification, so that users predict its behavior and understand the error messages it produces. Local type inference techniques attain this simplicity by inferring missing type information only from the types of adjacent
Quantifying Landscape Spatial Pattern: What Is the State of the Art?
, 1998
"... Landscape ecology is based on the premise that there are strong links between ecological pattern and ecological function and process. Ecological systems are spatially heterogeneous, exhibiting considerable complexity and variability in time and space. This variability is typically represented by cat ..."
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Cited by 186 (3 self)
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by categorical maps or by a collection of samples taken at specific spatial locations (point data). Categorical maps quantize variability by identifying patches that are relatively homogeneous and that exhibit a relatively abrupt transition to adjacent areas. Alternatively, pointdata analysis (geostatistics
Variable Reordering and Sifting for QMDD
"... This paper considers variable reordering for quantum multiplevalued decision diagrams (QMDD) used to represent the matrices describing reversible and quantum gates and circuits. An efficient method for adjacent variable interchange is presented and this method is employed to implement sifting of QM ..."
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This paper considers variable reordering for quantum multiplevalued decision diagrams (QMDD) used to represent the matrices describing reversible and quantum gates and circuits. An efficient method for adjacent variable interchange is presented and this method is employed to implement sifting
S.: Nilpotent adjacency matrices, random graphs, and quantum random variables
 2008) 155205. RENÉ SCHOTT AND G. STACEY STAPLES
"... For fixed n> 0, the space of finite graphs on n vertices is canonically associated with an abelian, nilpotentgenerated subalgebra of the 2nparticle fermion algebra. Using the generators of the subalgebra, an algebraic probability space of “nilpotent adjacency matrices ” associated with finite ..."
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Cited by 12 (10 self)
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graphs is defined. Each nilpotent adjacency matrix is a quantum random variable whosemth moment corresponds to the number ofmcycles in the graph G. Each matrix admits a canonical “quantum decomposition ” into a sum of three algebraic random variables: a = a∆+aΥ+aΛ, where a ∆ is classical while a
QMDD Minimization using Sifting for Variable Reordering
 In Journal of Multiplevalued Logic and Soft Computing
, 2007
"... This paper considers variable reordering for quantum multiplevalued decision diagrams (QMDDs) used to represent the matrices describing reversible/quantum gates and circuits. An efficient method for adjacent variable interchange is presented and this method is employed to implement a vertex reductio ..."
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Cited by 7 (5 self)
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This paper considers variable reordering for quantum multiplevalued decision diagrams (QMDDs) used to represent the matrices describing reversible/quantum gates and circuits. An efficient method for adjacent variable interchange is presented and this method is employed to implement a vertex
Adjacency Graph of the SNF as Source of Information
 in Proceedings of the 7th International Workshops on Boolean Problems, Freiberg University of Mining and Technology
, 2006
"... The Specialized Normal Form (SNF) is a unique (canonical) representation of Exclusive SumOfProducts (ESOP) expressions of a Boolean function. The adjacency graph of the SNF takes the cubes of the SNF as labels of the vertices and connects such vertices by an edge which differ exactly in one variab ..."
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Cited by 5 (5 self)
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variable of the associated cubes. It is known that each adjacency graph of the SNF of a Boolean function f: B k → B is a kregular graph. This paper shows, how differences between the vertices of this graph can be detected in order to find cubes from exact minimal ESOPs. 1
Are Adjacency Lists Worthwhile in AllDifferent?
, 2009
"... In our AllDifferent paper [3], there was a loose end. The graph algorithms always discover the graph as they traverse it, by querying variable domains. It might be more efficient to store the graph (and backtrack it) in the form of adjacency lists. This is done here, and we show that it doesn’t affe ..."
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In our AllDifferent paper [3], there was a loose end. The graph algorithms always discover the graph as they traverse it, by querying variable domains. It might be more efficient to store the graph (and backtrack it) in the form of adjacency lists. This is done here, and we show that it doesn
Spiraling of adjacent trajectories in chaotic systems
, 2004
"... The spiraling of adjacent trajectories in chaotic dynamical systems can be characterized by the distribution of local angular velocities of rotation of the displacement vector, which is governed by linearized equations of motion. This distribution, akin to that of local Lyapunov exponents, is studie ..."
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, is studied for three examples of threedimensional flows. Toy model shows that the rotation rate of adjacent trajectories influences on the rate of mixing of dynamic variables and on the sensitivity of trajectories to perturbations. PACS number: 05.45.a
Results 1  10
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