A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search [PDF]
Sensors, 2023 Currently, the widely used blind source separation algorithm is typically associated with issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly suitable for the separation of independent source signals.
Mingyang Tang, Yafeng Wu
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Blind Source Separation Based on Double-Mutant Butterfly Optimization Algorithm [PDF]
Sensors, 2022 The conventional blind source separation independent component analysis method has the problem of low-separation performance. In addition, the basic butterfly optimization algorithm has the problem of insufficient search capability. In order to solve the
Qingyu Xia +5 more
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Autoencoder based blind source separation for photoacoustic resolution enhancement [PDF]
Scientific Reports, 2020 Photoacoustics is a promising technique for in-depth imaging of biological tissues. However, the lateral resolution of photoacoustic imaging is limited by size of the optical excitation spot, and therefore by light diffraction and scattering.
Matan Benyamin +8 more
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JCCM: Joint conformer and CNN model for overlapping radio signals recognition
Electronics Letters, 2023 Overlapping radio signals recognition is attracting more attention as the development and ubiquitous application of radio technologies. The traditional blind signal separation (BSS) method is mostly not effective when both radio propagation effects and ...
Junbin Liang +5 more
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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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Underdetermined Blind Source Separation Algorithm for Speech Signal Based on DSKSVD Dictionary Learning [PDF]
Jisuanji gongcheng, 2018 In order to overcome the shortcoming that the traditional learning algorithm training has limited dictionary size and large amount of computation,the algorithm of underdetermined blind source separation for speech signal based on the dictionary learning ...
LI Hu,XU Yan
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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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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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