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MACH, V.; OZDOBINSKI, R.
Originální název
Optimizing dictionary learning parameters for solving Audio Inpainting problem
Anglický název
Druh
Článek recenzovaný mimo WoS a Scopus
Originální abstrakt
Recovering missing or distorted audio signal samples has been recently improved by solving an Audio Inpainting problem. This paper aims to connect this problem with K-SVD dictionary learning to improve reconstruction error for missing signal insertion problem. Our aim is to adapt an initial dictionary to the reliable signal to be more accurate in missing samples estimation. This approach is based on sparse signals reconstruction and optimization problem. In the paper two staple algorithms, connection between them and emerging problems are described. We tried to find optimal parameters for efficient dictionary learning.
Anglický abstrakt
Klíčová slova
Audio Inpainting, Dictionary Learning, K-SVD, Orthogonal Matching Pursuit, Signal reconstruction, Sparse Representations
Klíčová slova v angličtině
Autoři
Rok RIV
2014
Vydáno
07.01.2013
Místo
Brno
ISSN
1805-5443
Periodikum
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems
Svazek
2
Číslo
1
Stát
Česká republika
Strany od
40
Strany do
45
Strany počet
6
URL
http://www.ijates.org/index.php/ijates/article/view/34/32
BibTex
@article{BUT96562, author="Václav {Mach} and Roman {Ozdobinski}", title="Optimizing dictionary learning parameters for solving Audio Inpainting problem", journal="International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems", year="2013", volume="2", number="1", pages="40--45", issn="1805-5443", url="http://www.ijates.org/index.php/ijates/article/view/34/32" }