Zobrazeno 1 - 10
of 118
pro vyhledávání: '"Rajmic, P."'
Autor:
Kovanda, Vojtěch, Rajmic, Pavel
We propose a technique of signal acquisition using a combination of two devices with different sampling rates and quantization accuracies. Subsequent processing involving sparsity regularization enables us to reconstruct the signal at such a sampling
Externí odkaz:
http://arxiv.org/abs/2409.08071
The paper focuses on inpainting missing parts of an audio signal spectrogram. First, a recent successful approach based on an untrained neural network is revised and its several modifications are proposed, improving the signal-to-noise ratio of the r
Externí odkaz:
http://arxiv.org/abs/2409.06392
Autor:
Mokrý, Ondřej, Rajmic, Pavel
The paper presents an evaluation of popular audio inpainting methods based on autoregressive modeling, namely the extrapolation-based and Janssen methods. A novel variant of the Janssen method suitable for inpainting of gaps is also proposed. The mai
Externí odkaz:
http://arxiv.org/abs/2403.04433
A method for perfusion imaging with DCE-MRI is developed based on two popular paradigms: the low-rank + sparse model for optimisation-based reconstruction, and the deep unfolding. A learnable algorithm derived from a proximal algorithm is designed wi
Externí odkaz:
http://arxiv.org/abs/2312.07222
Publikováno v:
2023 46th International Conference on Telecommunications and Signal Processing (TSP)
Sasaki et al. (2018) presented an efficient audio declipping algorithm, based on the properties of Hankel-structure matrices constructed from time-domain signal blocks. We adapt their approach to solving the audio inpainting problem, where samples ar
Externí odkaz:
http://arxiv.org/abs/2303.18023
Autor:
Záviška, Pavel, Rajmic, Pavel
Publikováno v:
2022 45th International Conference on Telecommunications and Signal Processing (TSP)
We develop the analysis (cosparse) variant of the popular audio declipping algorithm of Siedenburg et al. (2014). Furthermore, we extend both the old and the new variants by the possibility of weighting the time-frequency coefficients. We examine the
Externí odkaz:
http://arxiv.org/abs/2205.10215
Publikováno v:
In Signal Processing February 2024 215
Publikováno v:
Elsevier Signal Processing, vol. 192, March 2022, 108365
Some audio declipping methods produce waveforms that do not fully respect the physical process of clipping, which is why we refer to them as inconsistent. This letter reports what effect on perception it has if the solution by inconsistent methods is
Externí odkaz:
http://arxiv.org/abs/2104.03074
Autor:
Petr Dejdar, Ondrej Mokry, Martin Cizek, Pavel Rajmic, Petr Munster, Jiri Schimmel, Lenka Pravdova, Tomas Horvath, Ondrej Cip
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Fiber optic infrastructure is essential in the transmission of data of all kinds, both for the long haul and shorter distances in cities. Optical fibers are also preferred for data infrastructures inside buildings, especially in highly secur
Externí odkaz:
https://doaj.org/article/ae42a45324d14686a8a89e130447fd45
Publikováno v:
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
The paper deals with the hitherto neglected topic of audio dequantization. It reviews the state-of-the-art sparsity-based approaches and proposes several new methods. Convex as well as non-convex approaches are included, and all the presented formula
Externí odkaz:
http://arxiv.org/abs/2010.16386