Displaying similar documents to “Wavelet based numerical homogenization.”

Haar wavelets method for solving Pocklington's integral equation

M. Shamsi, Mohsen Razzaghi, J. Nazarzadeh, Masoud Shafiee (2004)

Kybernetika

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A simple and effective method based on Haar wavelets is proposed for the solution of Pocklington’s integral equation. The properties of Haar wavelets are first given. These wavelets are utilized to reduce the solution of Pocklington’s integral equation to the solution of algebraic equations. In order to save memory and computation time, we apply a threshold procedure to obtain sparse algebraic equations. Through numerical examples, performance of the present method is investigated concerning...

Haar wavelet method for vibration analysis of nanobeams

M. Kirs, M. Mikola, A. Haavajõe, E. Õunapuu, B. Shvartsman, J. Majak (2016)

Waves, Wavelets and Fractals

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In the current study the Haar wavelet method is adopted for free vibration analysis of nanobeams. The size-dependent behavior of the nanobeams, occurring in nanostructures, is described by Eringen nonlocal elasticity model. The accuracy of the solution is explored. The obtained results are compared with ones computed by finite difference method. The numerical convergence rates determined are found to be in agreement with corresponding convergence theorems.

Numerical index with respect to an operator

Mohammad Ali Ardalani (2014)

Studia Mathematica

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We introduce new concepts of numerical range and numerical radius of one operator with respect to another one, which generalize in a natural way the known concepts of numerical range and numerical radius. We study basic properties of these new concepts and present some examples.

Wavelets and prediction in time series

Mošová, Vratislava

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Wavelets (see [2, 3, 4]) are a recent mathematical tool that is applied in signal processing, numerical mathematics and statistics. The wavelet transform allows to follow data in the frequency as well as time domain, to compute efficiently the wavelet coefficients using fast algorithm, to separate approximations from details. Due to these properties, the wavelet transform is suitable for analyzing and forecasting in time series. In this paper, Box-Jenkins models (see [1, 5]) combined...