Convex Combination
Mostrando 1-10 de 10 artigos, teses e dissertações.
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1. A Mixed-Integer convex formulation for production optimization of gas-lifted oil fields with routing and pressure constraints
Production optimization of gas-lifted oil fields under facility, routing, and pressure constraints has attracted the attention of researchers and practitioners for its scientific challenges and economic impact. The available methods fall into one of two categories: nonlinear or piecewise-linear approaches. The nonlinear methods optimize simulation models dir
Braz. J. Chem. Eng.. Publicado em: 2014-06
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2. Estratégias incrementais em combinação de filtros adaptativos. / Incremental strategies in combination of adaptive filters.
Neste trabalho uma nova estratégia de combinação de filtros adaptativos é apresentada e estudada. Inspirada por esquemas incrementais e filtragem adaptativa cooperativa, a combinação convexa usual de filtros em paralelo e independentes é reestruturada como uma configuração série-cooperativa, sem aumento da complexidade computacional. Dois novos alg
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 14/02/2012
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3. Combinação afim de algoritmos adaptativos. / Affine combination of adaptive algorithms.
In order to improve the performance of adaptive filters, the combination of algorithms is receiving much attention in the literature. This method combines linearly the outputs of two filters operating in parallel with different step-sizes to obtain an adaptive filter with fast convergence and reduced excess mean squared error (EMSE). In this context, it was
Publicado em: 2009
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4. Comparative study of spectral steplengths and nonmonotone linear searches / Estudo comparativo de passos espectrais e buscas lineares não monótonas
The Spectral Gradient method, introduced by Barzilai and Borwein and analized by Raydan for unconstrained minimization, is a simple method whose performance is comparable to traditional methods, such as conjugate gradients. Since the introduction of method, as well as its extension to minimization of convex sets, there were introduced various combinations of
Publicado em: 2008
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5. Robust filtering via convex combination of Kalman filters / Filtragem robusta via combinação convexa de filtros de Kalman
In this work, a new method to H2robust ?ltrer design is proposed. A convex combination of Kalman ?lters, calculated in each vertex of the uncertainty polytope, is used to synthesize the robust ?lter. For this model, the best one is calculated through a convex programming problem, expressed in terms of LMIs. Inicially a sub-class of polytopic systems is consi
Publicado em: 2007
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6. Filtragem robusta via combinação convexa de filtros de kalman / Robust filtering via convex combination of kalman filters
Neste trabalho, é proposto um novo método para o projeto de filtros robustos em norma H2, que consiste na utilização de uma combinação linear dos filtros de Kalman obtidos para os vértices do politopo de incertezas. Para esta classe de filtros, são obtidos problemas, expressos na forma de LMIs, para a determinação dos coeficientes que produzem o me
Publicado em: 2007
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7. A weighted projection centering method
An iterative method for finding the center of a linear programming polytope is presented. The method assumes that we start at a feasible interior point and each iterate is obtained as a convex combination of the orthogonal projection on the half spaces defined by the linear inequalities plus a special projections on the same half spaces. The algorithm is par
Computational & Applied Mathematics. Publicado em: 2003
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8. Otimização extrema generalizada: um novo algoritmo estocástico para o projeto ótimo / x
In this work a new numerical tool for application on optimal design is presented. Based on the theory of Self-Organized Criticality (SOC), it is intended to be used in problems that present complex characteristics such as a non-convex or even disjoint design space, the presence of multiple sub-optimal solutions on it, severe non-linearities on the objective
Publicado em: 2002
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9. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization
Given a dictionary D = {dk} of vectors dk, we seek to represent a signal S as a linear combination S = ∑k γ(k)dk, with scalar coefficients γ(k). In particular, we aim for the sparsest representation possible. In general, this requires a combinatorial optimization process. Previous work considered the special case where D is an overcomplete system consist
National Academy of Sciences.
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10. Isotropic probability measures in infinite-dimensional spaces
Every isotropic probability measure on the space R∞ of real sequences x = (x1, x2,...) is a convex combination of the measure concentrated at 0 and a member of I0(R∞), the set of all isotropic probability measures p∞ on R∞ with p∞({0}) = 0. Each p∞ [unk] I0(R∞) is completely determined by any one of its finite-dimensional marginal distributions