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31,987
Synchronous data flow
, 1987
"... Data flow is a natural paradigm for describing DSP applications for concurrent implementation on parallel hardware. Data flow programs for signal processing are directed graphs where each node represents a function and each arc represents a signal path. Synchronous data flow (SDF) is a special case ..."
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Cited by 622 (45 self)
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with data flow evaporates. Multiple sample rates within the same system are easily and naturally handled. Conditions for correctness of SDF graph are explained and scheduling algorithms are described for homogeneous parallel processors sharing memory. A preliminary SDF software system for automatically
Snakes, Shapes, and Gradient Vector Flow
 IEEE TRANSACTIONS ON IMAGE PROCESSING
, 1998
"... Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This paper presents a new extern ..."
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Cited by 755 (16 self)
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external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a graylevel or binary edge map derived from the image. It differs fundamentally from traditional snake external forces
A modular threedimensional finitedifference groundwater flow model
 U.S. Geological Survey Techniques of WaterResources Investigations Book 6, Chapter A1
, 1988
"... The primary objective of this course is to discuss the principals of finite difference methods and their applications in groundwater modeling. The emphasis of the class lectures is on the theoretical aspects of numerical modeling (finite difference method). Steps involved in simulation of groundwate ..."
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Cited by 508 (5 self)
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of groundwater systems under various initial/boundary conditions and management schemes will be practiced. The emphasis of the student presentations will be based on published papers concerning the applied aspects of groundwater computer modeling utilizing finite difference and analytical computer models
Cognitive networks
 IN PROC. OF IEEE DYSPAN 2005
, 2005
"... This paper presents a definition and framework for a novel type of adaptive data network: the cognitive network. In a cognitive network, the collection of elements that make up the network observes network conditions and then, using prior knowledge gained from previous interactions with the network ..."
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Cited by 1106 (7 self)
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This paper presents a definition and framework for a novel type of adaptive data network: the cognitive network. In a cognitive network, the collection of elements that make up the network observes network conditions and then, using prior knowledge gained from previous interactions
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
 Proc. Natl. Acad. Sci. USA
, 1990
"... ABSTRACT Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradientecho techniques in high fields, we demonstrate in vivo images of brain microvasculature with imag ..."
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Cited by 648 (1 self)
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with image contrast reflecting the blood oxygen level. This blood oxygenation leveldependent (BOLD) contrast follows blood oxygen changes induced by anesthetics, by insulininduced hypoglycemia, and by inhaled gas mixtures that alter metabolic demand or blood flow. The results suggest that BOLD contrast can
Fusion, Propagation, and Structuring in Belief Networks
 ARTIFICIAL INTELLIGENCE
, 1986
"... Belief networks are directed acyclic graphs in which the nodes represent propositions (or variables), the arcs signify direct dependencies between the linked propositions, and the strengths of these dependencies are quantified by conditional probabilities. A network of this sort can be used to repre ..."
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Cited by 484 (8 self)
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Belief networks are directed acyclic graphs in which the nodes represent propositions (or variables), the arcs signify direct dependencies between the linked propositions, and the strengths of these dependencies are quantified by conditional probabilities. A network of this sort can be used
II.A. Flow Condition
"... ProjectX is a highorder, adaptive discontinuous Galerkin finite element solver. The DG discretization uses Roe’s approximate Riemann solver1 for the inviscid numerical flux. The solution to the discretized system is obtained using a Newtonbased nonlinear solver with pseudotime continuation; howev ..."
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ProjectX is a highorder, adaptive discontinuous Galerkin finite element solver. The DG discretization uses Roe’s approximate Riemann solver1 for the inviscid numerical flux. The solution to the discretized system is obtained using a Newtonbased nonlinear solver with pseudotime continuation; however, due to the simplicity of this case, we employ a very high CFL number (106) to achieve nearNewton convergence. The linear system arising in each pseudotime step is solved using GMRES,2 preconditioned with an inplace blockILU(0) factorization3 with minimum discarded fill reordering and p = 0 algebraic coarse correction.4 An outputbased, anisotropic simplex mesh adaptation algorithm is used to control the discretization error.5 The algorithm iterates toward a mesh that minimizes the output error for a given number of degrees of freedom. The anisotropic adaptation decisions are entirely driven by the behavior of an outputbased a posteriori error estimate; thus, the method handles any discretization order, naturally incorporates both the primal and adjoint solution behaviors, and robustly treats irregular features. The output error estimate uses the dualweighted residual (DWR) method of Becker and Rannacher.6 A new mesh that conforms to the metric request is generated using using BAMG (Bidimensional Anisotropic Mesh Generator),7 and higherorder, globally curved meshes are constructed through linear elasticity.8 II. Case Description
Constant propagation with conditional branches
 ACM Transactions on Programming Languages and Systems
, 1991
"... Constant propagation is a wellknown global flow analysis problem. The goal of constant propagation is to discover values that are constant on all possible executions of a program and to propagate these constant values as far forward through the program as possible. Expressions whose operands are al ..."
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Cited by 355 (1 self)
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Constant propagation is a wellknown global flow analysis problem. The goal of constant propagation is to discover values that are constant on all possible executions of a program and to propagate these constant values as far forward through the program as possible. Expressions whose operands
INFLUENCE OF APPROACH FLOW CONDITIONS ON URBAN STREET CANYON FLOW
, 2014
"... Influence of approach flow conditions on urban street canyon flow ..."
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