Results 41 to 50 of about 4,267,953 (306)
Switching Independent Vector Analysis and its Extension to Blind and Spatially Guided Convolutional Beamforming Algorithms [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2021 This paper develops a framework that can accurately perform denoising, dereverberation, and source separation using a relatively small number of microphones. It has been empirically confirmed that Independent Vector Analysis (IVA) can blindly separate $N$
T. Nakatani +5 more
semanticscholar +1 more source
Infrasound Signal Classification Based on ICA and SVM [PDF]
Archives of Acoustics, 2023 A diagnostic technique based on independent component analysis (ICA), fast Fourier transform (FFT), and support vector machine (SVM) is suggested for effectively extracting signal features in infrasound signal monitoring.
Quanbo Lu, Meng Wang, Mei Li
doaj +1 more source
Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI Data
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2022 Identification of homogeneous subgroups of subjects plays a key role in the study of precision medicine. While there are a number of approaches based on the clustering of low-level features such as behavioral variables, work that makes use of fully ...
H. Yang +5 more
semanticscholar +1 more source
Independent Vector Analysis for Blind Deconvolving of Digital Modulated Communication Signals
Electronics, 2022 For the purpose of overcoming the random permutation ambiguity of the frequency-domain-independent component analysis (FDICA) for blind separation of convolutive mixtures, this paper proposes an independent vector analysis (IVA) detection receiver for ...
Zhongqiang Luo, Ruiming Guo, Chengjie Li
semanticscholar +1 more source
IEEE Access, 2020 By introducing a frequency dependence source prior including full-band and clique models, independent vector analysis (IVA) has been successfully used for convolutive blind source separation (BSS). In addition, independent low-rank matrix analysis (ILRMA)
Ui-Hyeop Shin, Hyung-Min Park
doaj +1 more source
Tracing Evolving Networks Using Tensor Factorizations vs. ICA-Based Approaches
Frontiers in Neuroscience, 2022 Analysis of time-evolving data is crucial to understand the functioning of dynamic systems such as the brain. For instance, analysis of functional magnetic resonance imaging (fMRI) data collected during a task may reveal spatial regions of interest, and ...
Evrim Acar +5 more
doaj +1 more source
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
core +1 more source
Speaker-independent negative emotion recognition [PDF]
, 2010 This work aims to provide a method able to distinguish between negative and non-negative emotions in vocal interaction. A large pool of 1418 features is extracted for that purpose. Several of those features are tested in emotion recognition for the first
Kotropoulos, C, Kotti, M, Paternò, F
core +1 more source
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.
core +2 more sources
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
doaj +1 more source