Displaying similar documents to “Stratified filtered sampling in stochastic optimization.”

A generalised approach to the use of sampling for rapid object location

E. R. Davies (2008)

International Journal of Applied Mathematics and Computer Science

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This paper has developed a generalised sampling strategy for the rapid location of objects in digital images. In this strategy a priori information on the possible locations of objects is used to guide the sampling process, and earlier body-based and edge-based approaches emerge automatically on applying the right a priori probability maps. In addition, the limitations of the earlier regular sampling technique have been clarified and eased - with the result that sampling patterns are...

Image sampling with quasicrystals.

Grundland, Mark, Patera, Jirí, Masáková, Zuzana, Dodgson, Neil A. (2009)

SIGMA. Symmetry, Integrability and Geometry: Methods and Applications [electronic only]

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Fixed precision optimal allocation in two-stage sampling

Wojciech Niemiro, Jacek Wesołowski (2001)

Applicationes Mathematicae

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Two-stage sampling schemes arise in survey sampling, especially in situations when the complete update of the frame is difficult. In this paper we solve the problem of fixed precision optimal allocation in two special two-stage sampling schemes. The solution is based on reducing the original question to an eigenvalue problem and then using the Perron-Frobenius theorem.

On some strategies using auxiliary information for estimating finite population mean.

L. N. Sahoo, J. Sahoo, Mariano Ruiz Espejo (1998)

Qüestiió

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This paper presents an empirical investigation of the performance of five strategies for estimating the finite population mean using parameters such as mean or variance or both of an auxiliary variable. The criteria used for the choices of these strategies are bias, efficiency and approach to normality (asymmetry).

Combining stochastic and deterministic approaches within high efficiency molecular simulations

Bruno Escribano, Elena Akhmatskaya, Jon Mujika (2013)

Open Mathematics

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Generalized Shadow Hybrid Monte Carlo (GSHMC) is a method for molecular simulations that rigorously alternates Monte Carlo sampling from a canonical ensemble with integration of trajectories using Molecular Dynamics (MD). While conventional hybrid Monte Carlo methods completely re-sample particle’s velocities between MD trajectories, our method suggests a partial velocity update procedure which keeps a part of the dynamic information throughout the simulation. We use shadow (modified)...

Dimensional Analysis in sampling inspection of merchandise

Drobot, Stefan, Warmus, Mieczysław

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I. Methodological remarks II. Dimensional analysis III. General principles of the theory IV. Sample size V. Aim of inspection and accordance with experience АНАЛИЗ РАЗМЕРНОСТИ В ВЫБОРОЧНОМ ИСПЫТАНИИ ТОВАРОВ (резюме)