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pro vyhledávání: '"Mokry P"'
Autor:
Mokrý, Ondřej, Rajmic, Pavel
Autoregressive (AR) modeling is invaluable in signal processing, in particular in speech and audio fields. Attempts in the literature can be found that regularize or constrain either the time-domain signal values or the AR coefficients, which is done
Externí odkaz:
http://arxiv.org/abs/2410.17790
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
Autor:
Zitzer, G., Tiedau, J., Okhapkin, M. V., Zhang, K., Mokry, C., Runke, J., Düllmann, Ch. E., Peik, E.
Publikováno v:
Phys. Rev. A 109, 033116 (2024)
Sympathetic cooling of Th$^{3+}$ ions is demonstrated in an experiment where $^{229}$Th and $^{230}$Th are extracted from uranium recoil ion sources and are confined in a linear Paul trap together with laser-cooled $^{88}$Sr$^+$ ions. Because of thei
Externí odkaz:
http://arxiv.org/abs/2312.05106
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
Let $G$ be a closed highly homogeneous subgroup of $S_{\infty}$ not involving circular orderings. We show that the closure of a conjugacy class from $G$ contains a conjugacy class which is comeagre in it. Furthermore, we show that the family of finit
Externí odkaz:
http://arxiv.org/abs/2303.07915
Audio inpainting, i.e., the task of restoring missing or occluded audio signal samples, usually relies on sparse representations or autoregressive modeling. In this paper, we propose to structure the spectrogram with nonnegative matrix factorization
Externí odkaz:
http://arxiv.org/abs/2206.13768
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
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