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Audio inpainting algorithms
Kolbábková, Anežka ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
Tato práce se zabývá doplňováním chybějících dat do audio signálů a algoritmy řešícími problém založenými na řídké reprezentaci audio signálu. Práce se zaměřuje na některé algoritmy, které řeší doplňování chybějících dat do audio signálů pomocí řídké reprezentace signálů. Součástí práce je také návrh algoritmu, který používá řídkou reprezentaci signálu a také nízkou hodnost signálu ve spektrogramu audio signálu. Dále práce uvádí implementaci tohoto algoritmu v programu Matlab a jeho vyhodnocení.
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Applications of sparse data representations
Navrátilová, Barbora ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
The goal of this thesis is to demonstrate practical application of sparse data representation in the processing of sparse signals. For solving several example problems - denoising, dequantization, and sparse signal decomposition - convex optimization was used. The solutions were implemented in the Matlab environment. For each of the problems, there are two solutions - one for one-dimensional, and one for two-dimensional signal.
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Making up missing audio signal sections
Pospíšil, Jiří ; Rášo, Ondřej (referee) ; Mach, Václav (advisor)
The goal of this bachelor’s thesis is to get introduced with methods for reconstruction of missing samples in audio signal using periodicity-based interpolation and AR model based interpolation. Further it’s introducing us with Audio Inpainting method based on sparse representation. In practical part there are programmed three algorithms based on these interpolation methods and described an algorithm which is used in Audio Inpainting. These algorithms are compared with objective methods, SNR measurements depending on gap length and value of input parameter.
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Optimization of data representation for target tracking using sensor network
Cabalová, Klára ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
The aim of this bachelor thesis is to find optimal data representation for target tracking using sensor network. There is described a model of decentralized sensor network and also the application of so called dictionary to represent the measured data. Also, there is theoretically introduced the K-SVD algorithm that is used for dictionary learning and there are learnt dictionaries for data representation based on the model signals. These dictionaries are compared with each other.
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Optimization of data representation for target tracking using sensor network
Cabalová, Klára ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
The aim of this bachelor thesis is to find optimal data representation for target tracking using sensor network. There is described a model of decentralized sensor network and also the application of so called dictionary to represent the measured data. Also, there is theoretically introduced the K-SVD algorithm that is used for dictionary learning and there are learnt dictionaries for data representation based on the model signals. These dictionaries are compared with each other.
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Making up missing audio signal sections
Pospíšil, Jiří ; Rášo, Ondřej (referee) ; Mach, Václav (advisor)
The goal of this bachelor’s thesis is to get introduced with methods for reconstruction of missing samples in audio signal using periodicity-based interpolation and AR model based interpolation. Further it’s introducing us with Audio Inpainting method based on sparse representation. In practical part there are programmed three algorithms based on these interpolation methods and described an algorithm which is used in Audio Inpainting. These algorithms are compared with objective methods, SNR measurements depending on gap length and value of input parameter.
|
|
|
Applications of sparse data representations
Navrátilová, Barbora ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
The goal of this thesis is to demonstrate practical application of sparse data representation in the processing of sparse signals. For solving several example problems - denoising, dequantization, and sparse signal decomposition - convex optimization was used. The solutions were implemented in the Matlab environment. For each of the problems, there are two solutions - one for one-dimensional, and one for two-dimensional signal.
|
|
|
Audio inpainting algorithms
Kolbábková, Anežka ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
Tato práce se zabývá doplňováním chybějících dat do audio signálů a algoritmy řešícími problém založenými na řídké reprezentaci audio signálu. Práce se zaměřuje na některé algoritmy, které řeší doplňování chybějících dat do audio signálů pomocí řídké reprezentace signálů. Součástí práce je také návrh algoritmu, který používá řídkou reprezentaci signálu a také nízkou hodnost signálu ve spektrogramu audio signálu. Dále práce uvádí implementaci tohoto algoritmu v programu Matlab a jeho vyhodnocení.
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