Results 21 to 30 of about 451,315 (310)
TBSSvis: Visual analytics for Temporal Blind Source Separation
Visual Informatics, 2022 Temporal Blind Source Separation (TBSS) is used to obtain the true underlying processes from noisy temporal multivariate data, such as electrocardiograms.
Nikolaus Piccolotto +6 more
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Graph Signal Processing Meets Blind Source Separation [PDF]
IEEE Transactions on Signal Processing, 2020 In graph signal processing (GSP), prior information on the dependencies in the signal is collected in a graph which is then used when processing or analyzing the signal.
J. Miettinen +3 more
semanticscholar +1 more source
IEEE/ACM Transactions on Audio Speech and Language Processing, 2020 This article describes a computationally-efficient blind source separation (BSS) method based on the independence, low-rankness, and directivity of the sources.
Kouhei Sekiguchi +4 more
semanticscholar +1 more source
Consistent independent low-rank matrix analysis for determined blind source separation [PDF]
EURASIP Journal on Advances in Signal Processing, 2020 Independent low-rank matrix analysis (ILRMA) is the state-of-the-art algorithm for blind source separation (BSS) in the determined situation (the number of microphones is greater than or equal to that of source signals). ILRMA achieves a great separation
Daichi Kitamura, K. Yatabe
semanticscholar +1 more source
Blind wideband source separation [PDF]
Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002 This paper deals with the general problem of separating two independent wideband sources when they are mixed by unknown filters. In order to solve this problem, a backward framework is proposed which is composed of two different stages. The first one consists of two linear predictors devoted to improve the source separation, whitening the input signals.
Nájar Martón, Montserrat +2 more
openaire +2 more sources
Blind Source Separation Based on Improved Wave-U-Net Network
IEEE Access, 2023 With the development and widespread application of voice interaction technology, it has become crucial to improve the accuracy of blind source separation technology.
Chaofeng Lan +3 more
doaj +1 more source
Group-level component analyses of EEG: validation and evaluation
Frontiers in Neuroscience, 2015 Multi-subject or group-level component analysis provides a data-driven approach to study properties of brain networks. Algorithms for group-level data decomposition of functional magnetic resonance imaging data have been brought forward more than a ...
Rene eHuster +5 more
doaj +1 more source
Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming
Sensors, 2021 Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed ...
Henglin Pu +5 more
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Blind Audio Source Separation With Minimum-Volume Beta-Divergence NMF [PDF]
IEEE Transactions on Signal Processing, 2019 Considering a mixed signal composed of various audio sources and recorded with a single microphone, we consider in this paper the blind audio source separation problem which consists in isolating and extracting each of the sources.
V. Leplat, Nicolas Gillis, A. Ang
semanticscholar +1 more source
Unified left eigenvector (ULEV) for blind source separation
Electronics Letters, 2022 A joint analysis method is proposed for source separation from multiple datasets. In this method, sources with the greatest impact on the multiple datasets are identified and then are sequentially separated. The method utilizes the advantage of structure
Erfan Naghsh +2 more
doaj +1 more source