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Autor
Cuomo Salvatore (University of Naples Federico II, Italy), Farina Raffaele (Institute for high performance computing and networking CNR, Italy), Galletti Ardelio (Institute for high performance computing and networking CNR, Italy), Marcellino Livia (Institute for high performance computing and networking CNR, Italy)
Tytuł
A K-iterated scheme for the First-order Gaussian Recursive Filter with Boundary Conditions
Źródło
Annals of Computer Science and Information Systems, 2015, vol. 5, s. 641-647, rys., tab., bibliogr. 16 poz.
Słowa kluczowe
Algorytmy
Algorithms
Uwagi
summ.
Abstrakt
Recursive Filters (RFs) are a well known way to approximate the Gaussian convolution and are intensively used in several research fields. When applied to signals with support in a finite domain, RFs can generate distortions and artifacts, mostly localized at the boundaries of the computed solution. To deal with this issue, heuristic and theoretical end conditions have been proposed in literature. However, these end conditions strategies do not consider the case in which a Gaussian RF is applied more than once, as often happens in several realistic applications. In this paper, we suggest a way to use the end conditions for such a K-iterated Gaussian RF and propose an algorithm that implements the described approach. Tests and numerical experiments show the benefit of the proposed scheme.(original abstract)
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Bibliografia
Pokaż
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  2. S. Cuomo, G. De Pietro, R. Farina, A. Galletti, and G. Sannino - A framework for ECG denoising for mobile devices. PETRA 15 ACM. ISBN 978-1-4503-3452-5/15/07, doi: 10.1145/2769493.2769560, 2015.
  3. S. Cuomo, R. Farina, A. Galletti, L. Marcellino -An error estimate of Gaussian Recursive Filter in 3Dvar problem, Federated Conference on Computer Science and Information Systems, FedCSIS 2014, doi: 10.15439/2014F279, pp. 587-595, 2014.
  4. L. D'Amore, R. Arcucci, L. Marcellino, A. Murli- HPC computation issues of the incremental 3D variational data assimilation scheme in OceanVarsoftware. Journal of Numerical Analysis, Industrial and Applied Mathematics, 7(3-4), pp. 91-105, 2013.
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  6. S. Dobricic, N. Pinardi - An oceanographic three-dimensional variational data assimilation scheme. Ocean Modeling 22, pp. 89-105, doi: 10.1016/j.ocemod.2008.01.004, 2008.
  7. Farina, R., Dobricic, S., Storto, A., Masina, S., Cuomo, S. -A revised scheme to compute horizontal covariances in an oceanographic 3DVAR assimilation system. Journal of Computational Physics, 284, pp. 631-647, doi: 10.1016/j.jcp.2015.01.003, 2015.
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  10. R.J. Purser, W.-S. Wu, D.F. Parrish, N.M. Roberts - Numerical Aspects of the Application of Recursive Filters to Variational Statistical Analysis. Part I: Spatially Homogeneous and Isotropic Gaussian Covariances. Monthly Weather Review 131, pp. 1524-1535, doi: 10.1175//2543.1, 2003.
  11. C. Hayden, R. Purser - Recursive filter objective analysis of meteorological field: applications to NESDIS operational processing. Journal of Applied Meteorology 34, pp. 3-15, doi: 10.1175/1520-0450-34.1.3, 1995.
  12. L.V. Vliet, I. Young, P. Verbeek - Recursive Gaussian derivative filters. International Conference Recognition, pp. 509-514, doi: 10.1109/ICPR.1998.711192, 1998.
  13. L.J. van Vliet, P.W. Verbeek - Estimators for orientation and anisotropy in digitized image. Proc. ASCI'95, Heijen , pp. 442-450, 1995.
  14. B. Triggs, M. Sdika - Boundary conditions for Young-van Vliet recursive filtering. IEEE Transactions on Signal Processing, 54 (6 I), pp. 2365- 2367, doi: 10.1109/TSP.2006.871980, 2006.
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  16. I.T. Young, L.J. van Vliet - Recursive implementation of the Gaussian filter. Signal Processing 44, pp. 139-151, doi: 10.1016/0165- 1684(95)00020-E, 1995.
Cytowane przez
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ISSN
2300-5963
Język
eng
URI / DOI
http://dx.doi.org/10.15439/2015F286
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