Independent Vector Analysis with More Microphones Than Sources [PDF]
2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2019 We extend frequency-domain blind source separation based on independent vector analysis to the case where there are more microphones than sources. The signal is modelled as non-Gaussian sources in a Gaussian background. The proposed algorithm is based on a parametrization of the demixing matrix decreasing the number of parameters to estimate ...
Scheibler, Robin, Ono, Nobutaka
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Results on lattice vector quantization with dithering [PDF]
, 1996 The statistical properties of the error in uniform scalar quantization have been analyzed by a number of authors in the past, and is a well-understood topic today. The analysis has also been extended to the case of dithered quantizers, and the advantages
Kiraç, Ahmet, Vaidyanathan, P. P.
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Leptoquark Pair Production at $ep$ Colliders [PDF]
, 1994 The pair production cross section for scalar and vector leptoquarks at $ep$ colliders is calculated for the case of photon--gluon fusion. In a model independent analysis we consider the most general $C$ and $P$ conserving couplings of gluons and photons ...
Blümlein, Johannes +2 more
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Hybrid Source Prior Based Independent Vector Analysis for Blind Separation of Speech Signals
IEEE Access, 2020 Blind Source Separation (BSS) application is a delinquent issue in a complex reverberant environment with changing room geometric dimensions and an increasing number of speech sources.
Junaid Bahadar Khan +3 more
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Interaction of the vector-meson octet with the baryon octet in effective field theory [PDF]
, 2015 We analyze the constraint structure of the interaction of vector mesons with baryons using the classical Dirac constraint analysis. We show that the standard interaction in terms of two independent SU(3) structures is consistent at the classical level ...
Kucukarslan, A., Scherer, S., Unal, Y.
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Spatial Dynamic Functional Connectivity Analysis Identifies Distinctive Biomarkers in Schizophrenia
Frontiers in Neuroscience, 2019 Dynamic functional network connectivity (dFNC) analysis is a widely-used to study associations between dynamic functional correlations and cognitive abilities.
Suchita Bhinge +4 more
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Preserving Subject Variability in Group fMRI Analysis: Performance Evaluation of GICA versus IVA
Frontiers in Systems Neuroscience, 2014 Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI ...
Andrew eMichael +6 more
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Blind Audio Source Separation Using Independent Component Analysis and Independent Vector Analysis
International Journal of Applied Mathematics, Electronics and Computers, 2016 Blind Source Separation (BSS) is one of the most important andchallenging problem for the researchers in audio and speech processing area. Inthe literature, many different methods have been proposed to solve BSS problem.In this study, we have compared the performance of three popular BSS methodsbased on Independent Component Analysis (ICA) and ...
MAHDİ, Alyaa +2 more
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Present Bounds on New Neutral Vector Resonances from Electroweak Gauge Boson Pair Production at the LHC [PDF]
, 2011 Several extensions of the Standard Model predict the existence of new neutral spin-1 resonances associated to the electroweak symmetry breaking sector.
Eboli, O. J. P. +2 more
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Independent Component Analysis and Number of Independent Basis Vectors
Procedia Computer Science, 2015 AbstractAmong the various biometric systems, face recognition is an important area of research due to its applications in Human Computer Interaction, biometrics and security. It is one of the most popular research areas in the field of computer vision and pattern recognition.
Borade, Sushma Niket +2 more
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