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Yuri K.Dem’yanovich



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Yuri K.Dem’yanovich


WSEAS Transactions on Mathematics


Print ISSN: 1109-2769
E-ISSN: 2224-2880

Volume 18, 2019

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


Volume 18, 2019



Parallelization of Spline-Wavelet Decomposition

AUTHORS: Yuri K.Dem’yanovich

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A discrete spline-wavelet decomposition of the first order is discussed in the framework of the nonclassical approach. The purpose of this paper is to estimate the calculation duration for the discrete spline-wavelet decomposition with the use of two sorts of computers: One-Processor System (OPS) and Parallel Multi-processor System (PMS). The main object is the grid functions, which are named flows. The finite dimensional spaces of the initial flows, wavelet flows and main flows are introduced. These spaces are associated with the original and the enlarged grids, respectively. Estimates for the duration of the calculations are given with taking into account the properties of a communication computer environment. The presentation is accompanied with illustrative examples. We consider the grid functions whose domain is a grid on the real axis (for example, on the set of integers). This approach is convenient when processing flows are sequences of numbers. Then we discuss a grid enlargement and construct an embedded discrete spline space. Using a projection operator, we obtain a wavelet decomposition and give an illustration example of the mentioned decomposition. Taking into account the obtained algorithms we consider their implementation with OPS and PMS. In the situation of the unlimited concurrency the duration (runtime) of calculation with PMS does not depend on the data volume (i.e. it does not depend on the length of the initial flow), on the other hand, the duration of the calculation with OPS is directly proportional to the data volume.

KEYWORDS: spline-wavelet decomposition, parallelization, runtime, duration of calculation

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WSEAS Transactions on Mathematics, ISSN / E-ISSN: 1109-2769 / 2224-2880, Volume 18, 2019, Art. #33, pp. 241-249


Copyright Β© 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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