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CBS constants for graph-Laplacians and application to multilevel methods for discontinuous Galerkin systems

by R. Lazarov, S. Margenov - J. Complexity , 2006
"... Abstract. The goal of this work is to derive and justify a multilevel preconditioner for symmetric discontinuous approximations of second order elliptic problems. Our approach is based on the following simple idea. The finite element space V of piece-wise polynomials of certain degree that are disco ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
of the discontinuous Galerkin system in spirit of the work [4] of Axelsson and Vassilevski. key words: discontinuous Galerkin, second order elliptic equation, graph-Laplacian, multilevel preconditioning, CBS constant (1.1) 1.

Bundle Adjustment -- A Modern Synthesis

by Bill Triggs, Philip McLauchlan, Richard Hartley, Andrew Fitzgibbon - VISION ALGORITHMS: THEORY AND PRACTICE, LNCS , 2000
"... This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics c ..."
Abstract - Cited by 555 (12 self) - Add to MetaCart
covered include: the choice of cost function and robustness; numerical optimization including sparse Newton methods, linearly convergent approximations, updating and recursive methods; gauge (datum) invariance; and quality control. The theory is developed for general robust cost functions rather than

Convex Analysis

by R. Tyrrell Rockafellar , 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
Abstract - Cited by 5350 (67 self) - Add to MetaCart
was the exploration of variations around a point, within the bounds imposed by the constraints, in order to help characterize solutions and portray them in terms of ‘variational principles’. Notions of perturbation, approximation and even generalized differentiability were extensively investigated. Variational theory

Chebyshev and Fourier Spectral Methods

by John P. Boyd , 1999
"... ..."
Abstract - Cited by 778 (12 self) - Add to MetaCart
Abstract not found

Community detection in graphs

by Santo Fortunato , 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
Abstract - Cited by 801 (1 self) - Add to MetaCart
The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices

A Signal Processing Approach To Fair Surface Design

by Gabriel Taubin , 1995
"... In this paper we describe a new tool for interactive free-form fair surface design. By generalizing classical discrete Fourier analysis to two-dimensional discrete surface signals -- functions defined on polyhedral surfaces of arbitrary topology --, we reduce the problem of surface smoothing, or fai ..."
Abstract - Cited by 668 (15 self) - Add to MetaCart
In this paper we describe a new tool for interactive free-form fair surface design. By generalizing classical discrete Fourier analysis to two-dimensional discrete surface signals -- functions defined on polyhedral surfaces of arbitrary topology --, we reduce the problem of surface smoothing, or fairing, to low-pass filtering. We describe a very simple surface signal low-pass filter algorithm that applies to surfaces of arbitrary topology. As opposed to other existing optimization-based fairing methods, which are computationally more expensive, this is a linear time and space complexity algorithm. With this algorithm, fairing very large surfaces, such as those obtained from volumetric medical data, becomes affordable. By combining this algorithm with surface subdivision methods we obtain a very effective fair surface design technique. We then extend the analysis, and modify the algorithm accordingly, to accommodate different types of constraints. Some constraints can be imposed without any modification of the algorithm, while others require the solution of a small associated linear system of equations. In particular, vertex location constraints, vertex normal constraints, and surface normal discontinuities across curves embedded in the surface, can be imposed with this technique. CR Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/image generation - display algorithms; I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling - curve, surface, solid, and object representations;J.6[Com- puter Applications]: Computer-Aided Engineering - computeraided design General Terms: Algorithms, Graphics. 1

SIS: A System for Sequential Circuit Synthesis

by Ellen M. Sentovich, Kanwar Jit Singh, Luciano Lavagno, Cho Moon, Rajeev Murgai, Alexander Saldanha, Hamid Savoj, Paul R. Stephan, Robert K. Brayton, Alberto Sangiovanni-Vincentelli , 1992
"... SIS is an interactive tool for synthesis and optimization of sequential circuits. Given a state transition table, a signal transition graph, or a logic-level description of a sequential circuit, it produces an optimized net-list in the target technology while preserving the sequential input-output b ..."
Abstract - Cited by 514 (41 self) - Add to MetaCart
SIS is an interactive tool for synthesis and optimization of sequential circuits. Given a state transition table, a signal transition graph, or a logic-level description of a sequential circuit, it produces an optimized net-list in the target technology while preserving the sequential input

Reversible Markov chains and random walks on graphs

by David Aldous, James Allen Fill , 2002
"... ..."
Abstract - Cited by 549 (13 self) - Add to MetaCart
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The Elements of Statistical Learning -- Data Mining, Inference, and Prediction

by Trevor Hastie, Robert Tibshirani, Jerome Friedman
"... ..."
Abstract - Cited by 1320 (13 self) - Add to MetaCart
Abstract not found

Visual reconstruction

by Andrew Blake, Andrew Zisserman , 1987
"... ..."
Abstract - Cited by 891 (3 self) - Add to MetaCart
Abstract not found
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