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Spatially-Regularized Switching Independent Vector Analysis
2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2023This paper proposes a novel algorithm that uses spatial regularization and a switching filter to enhance the separation accuracy of Independent Vector Analysis (IVA) with specified source permutation based on prior knowledge of sources’ Directions-of ...
Tetsuya Ueda +4 more
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Spatially Guided Independent Vector Analysis
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020We present a Maximum A Posteriori (MAP) derivation of the Independent Vector Analysis (IVA) algorithm for blind source separation incorporating an additional spatial prior over the demixing matrices. In this way, the outer permutation ambiguity of IVA is avoided and the algorithm can be guided towards a desired solution in adverse acoustic conditions ...
Andreas Brendel +2 more
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Independent vector analysis: Model, applications, challenges
Pattern Recognition, 2023Zhongqiang Luo
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Performance Bounds for Complex-Valued Independent Vector Analysis
IEEE Transactions on Signal Processing, 2020Independent Vector Analysis (IVA) is a method for joint Blind Source Separation of multiple datasets with wide area of applications including audio source separation, biomedical data analysis, etc. In this paper, identification conditions and Cramer-Rao Lower Bound (CRLB) on the achievable accuracy are derived for the complex-valued case involving ...
Vaclav Kautsky +3 more
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Sparse Independent Vector Analysis Based on Mel Filter
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE), 2020To make independent vector analysis (IVA) robust for whitening, sparse IVA clips spectrum in high frequency bands, because whitening generates artificial noise in high frequency bands. In this paper, to avoid clipping of source spectrum by sparse IVA, we propose an application of Mel filter to the observed spectrum before clipping in order to emphasize
Takahiro Ushijima +3 more
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European Signal Processing Conference, 2022
In this paper, we propose an alternative algorithm, which is faster and more stable, for geometrically constrained independent vector analysis (GC-IVA) to tackle multichannel speech separation problem. GC-IVA is a method that combines IVA, a blind source
Kana Goto +4 more
semanticscholar +1 more source
In this paper, we propose an alternative algorithm, which is faster and more stable, for geometrically constrained independent vector analysis (GC-IVA) to tackle multichannel speech separation problem. GC-IVA is a method that combines IVA, a blind source
Kana Goto +4 more
semanticscholar +1 more source
China Communications, 2022
In application to time convolutive mixing model or frequency domain blind separation model for wireless receiving applications, frequency domain independent component analysis (FDICA) has been a very popular method but with adverse random permutation ...
Zhongqiang Luo, Mingchun Li, Chengjie Li
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In application to time convolutive mixing model or frequency domain blind separation model for wireless receiving applications, frequency domain independent component analysis (FDICA) has been a very popular method but with adverse random permutation ...
Zhongqiang Luo, Mingchun Li, Chengjie Li
semanticscholar +1 more source
International Workshop on Acoustic Signal Enhancement, 2022
Acoustic vector sensor (AVS), as a compact sensor with the capability of forming a frequency-invariant spatial beampattern over the 3D space, has potential in source separation.
Yichen Yang +3 more
semanticscholar +1 more source
Acoustic vector sensor (AVS), as a compact sensor with the capability of forming a frequency-invariant spatial beampattern over the 3D space, has potential in source separation.
Yichen Yang +3 more
semanticscholar +1 more source