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Compression of satellite data.

Roberto Barrio, Antonio Elipe (2002)

Revista Matemática Complutense

In this paper, we present the simple and double compression algorithms with an error control for compressing satellite data corresponding to several revolutions. The compressions are performed by means of approximations in the norm L∞ by finite series of Chebyshev polynomials, with their known properties of fast evaluation, uniform distribution of the error, and validity over large intervals of time. By using the error control here introduced, the number of terms of the series is given automatically...

Computation of the distance to semi-algebraic sets

Christophe Ferrier (2010)

ESAIM: Control, Optimisation and Calculus of Variations

This paper is devoted to the computation of distance to set, called S, defined by polynomial equations. First we consider the case of quadratic systems. Then, application of results stated for quadratic systems to the quadratic equivalent of polynomial systems (see [5]), allows us to compute distance to semi-algebraic sets. Problem of computing distance can be viewed as non convex minimization problem: d ( u , S ) = inf x ∈ S ∥ x - u ∥ 2 , where u is in ℛ n . To have, at least, lower approximation of distance, we consider the dual...

Computing and proving with pivots

Frédéric Meunier (2013)

RAIRO - Operations Research - Recherche Opérationnelle

A simple idea used in many combinatorial algorithms is the idea of pivoting. Originally, it comes from the method proposed by Gauss in the 19th century for solving systems of linear equations. This method had been extended in 1947 by Dantzig for the famous simplex algorithm used for solving linear programs. From since, a pivoting algorithm is a method exploring subsets of a ground set and going from one subset σ to a new one σ′ by deleting an element inside σ and adding an element outside σ: σ′ = σv}  ∪  {u},...

Computing minimum norm solution of a specific constrained convex nonlinear problem

Saeed Ketabchi, Hossein Moosaei (2012)

Kybernetika

The characterization of the solution set of a convex constrained problem is a well-known attempt. In this paper, we focus on the minimum norm solution of a specific constrained convex nonlinear problem and reformulate this problem as an unconstrained minimization problem by using the alternative theorem.The objective function of this problem is piecewise quadratic, convex, and once differentiable. To minimize this function, we will provide a new Newton-type method with global convergence properties....

Computing the greatest 𝐗 -eigenvector of a matrix in max-min algebra

Ján Plavka (2016)

Kybernetika

A vector x is said to be an eigenvector of a square max-min matrix A if A ⊗ x = x . An eigenvector x of A is called the greatest 𝐗 -eigenvector of A if x ∈ 𝐗 = { x ; x ̲ ≤ x ≤ x ¯ } and y ≤ x for each eigenvector y ∈ 𝐗 . A max-min matrix A is called strongly 𝐗 -robust if the orbit x , A ⊗ x , A 2 ⊗ x , ⋯ reaches the greatest 𝐗 -eigenvector with any starting vector of 𝐗 . We suggest an O ( n 3 ) algorithm for computing the greatest 𝐗 -eigenvector of A and study the strong 𝐗 -robustness. The necessary and sufficient conditions for strong 𝐗 -robustness are introduced and an efficient...

Computing the Stackelberg/Nash equilibria using the extraproximal method: Convergence analysis and implementation details for Markov chains games

Kristal K. Trejo, Julio B. Clempner, Alexander S. Poznyak (2015)

International Journal of Applied Mathematics and Computer Science

In this paper we present the extraproximal method for computing the Stackelberg/Nash equilibria in a class of ergodic controlled finite Markov chains games. We exemplify the original game formulation in terms of coupled nonlinear programming problems implementing the Lagrange principle. In addition, Tikhonov's regularization method is employed to ensure the convergence of the cost-functions to a Stackelberg/Nash equilibrium point. Then, we transform the problem into a system of equations in the...

Condiciones necesarias de optimalidad en programación semi-infinita lineal: cualificaciones de restricciones y propiedades del conjunto posible.

Teresa León, Enriqueta Vercher (1994)

Qüestiió

En este trabajo se establece una caracterización de las soluciones óptimas para el problema continuo de Programación Semi-Infinita Lineal, donde el conjunto de índices es un compacto de Rp. Para la demostración de la condición necesaria de optimalidad se ha utilizado una extensión de la cualificación de restricciones de Mangasarian-Fromovitz. Hemos probado que dicha cualificación es imprescindible para asegurar que no hay desigualdades inestables en el conjunto posible y para que existan puntos...

Condiciones suficientes para la existencia de solución óptima en un programa semi-infinito.

Miguel Angel Goberna Torrent, Jesús T. Pastor Ciurana (1983)

Trabajos de Estadística e Investigación Operativa

Bajo condiciones muy generales, la acotación del conjunto factible en un problema de Programación Semi-Infinita garantiza la existencia de solución óptima del problema. Por ello, se estudian en la primera parte condiciones suficientes para la acotación del conjunto de soluciones de un sistema de infinitas ecuaciones. En la segunda parte se dan condiciones de diversa índole que involucran a la función objetivo de distintas maneras, a saber, a través de la función de Lagrange asociada al problema,...

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