Results 21 to 30 of about 167,965 (293)
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
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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
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
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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
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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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
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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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EURASIP Journal on Audio, Speech, and Music Processing, 2010 Frequency-domain blind source separation (BSS) performs poorly in high reverberation because the independence assumption collapses at each frequency bins when the number of bins increases.
Lin Wang, Heping Ding, Fuliang Yin
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Blind Source Separation based on Whale Optimization Algorithm
MATEC Web of Conferences, 2018 Aiming at the problem of linear instantaneous aliasing in blind source separation, a new method of blind signal separation using whale optimization algorithm is proposed in this paper, which provides a new research idea and method for blind signal ...
Ding-li CHU, Hong CHEN, Han-yi CHEN
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