Results 181 to 190 of about 1,709,161 (224)
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On the optimality of linear schedules
Journal of VLSI signal processing systems for signal, image and video technology, 1989An algorithm can be modeled as a set of indexed computations, and a schedule is a mapping of the algorithm index space into time.Linear schedules are a special class of schedules that are described by a linear mapping and are commonly used in many systolic algorithms.Free schedules cause computations of an algorithm to execute as soon as their operands
Weijia Shang, José A. B. Fortes
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Journal of Algorithms, 1993
Summary: Let \(\Gamma_ 0\) be a set of \(n\) halfspaces in \(E^ d\) (where the dimension \(d\) is fixed) and let \(m\) be a parameter, \(n\leq m\leq n^{\lfloor d/2\rfloor}\). We show that \(\Gamma_ 0\) can be preprocessed in time and space \(0(m^{1+\delta}\)) (for any fixed \(\delta>0\)) so that given a vector \(c\in E^ d\) and another set \(\Gamma_ q\)
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Summary: Let \(\Gamma_ 0\) be a set of \(n\) halfspaces in \(E^ d\) (where the dimension \(d\) is fixed) and let \(m\) be a parameter, \(n\leq m\leq n^{\lfloor d/2\rfloor}\). We show that \(\Gamma_ 0\) can be preprocessed in time and space \(0(m^{1+\delta}\)) (for any fixed \(\delta>0\)) so that given a vector \(c\in E^ d\) and another set \(\Gamma_ q\)
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Optimal Linearization in Holography
Applied Optics, 1969Optimal linearization in holography is studied from the nonlinear system theory point of view. A generalized optimal linearization method for a physical photographic emulsion is presented. A generalized first-order amplitude transmittance (i.e., the generalized transfer function) with respect to the input irradiance is determined.
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Computing, 1980
Two methods for solving an optimization problem with piecewise linear, convex, and continuous objective function and linear restrictions are described. The first one represents a generalization of the ordinary Simplex-Algorithm by Dantzig, the second one an adaptation of the Reduced Gradient Method by P. Wolfe to the discussed problem.
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Two methods for solving an optimization problem with piecewise linear, convex, and continuous objective function and linear restrictions are described. The first one represents a generalization of the ordinary Simplex-Algorithm by Dantzig, the second one an adaptation of the Reduced Gradient Method by P. Wolfe to the discussed problem.
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Abstract Optimal Linear Filtering
SIAM Journal on Control and Optimization, 2000The linear optimal filtering problems in infinite-dimensional Hilbert spaces and their extensions are investigated. The quality functional is allowed to be a general quadratic functional defined by a possibly degenerate operator. The solutions of the stable and the causal filtering problems are obtained.
Vladimir N. Fomin, Michael V. Ruzhansky
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Linear and Integer Linear Optimization
1999This is a textbook about linear and integer linear optimization. The major goal is to develop the theory of linear and integer linear optimization in a unified manner and then demonstrate how to use this theory to solve very large real world problems.
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An interval sequential linear programming for nonlinear robust optimization problems
Applied Mathematical Modelling, 2022Jiachang Tang, Chunming Fu, Haibo Liu
exaly
1994
Abstract Optimization is itself a large area within the field of applied mathematics. It deals with the minimization and maximization of functions with or without constraints and has many different applications. A large number of these applications belong to the area of operations research within the economic sciences.
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Abstract Optimization is itself a large area within the field of applied mathematics. It deals with the minimization and maximization of functions with or without constraints and has many different applications. A large number of these applications belong to the area of operations research within the economic sciences.
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