Results 11 to 20 of about 4,259 (92)
Independent Vector Analysis Inspired Amateur Drone Detection Through Acoustic Signals
IEEE Access, 2021 Detection of amateur drones (AmDrs) is mandatory requirement of various defence organizations and is also required to protect human life. In literature, various researchers contributed in this regard and developed different algorithms utilizing video ...
Zahoor Uddin +3 more
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A Survey of Optimization Methods for Independent Vector Analysis in Audio Source Separation
Sensors, 2023 With the advent of the era of big data information, artificial intelligence (AI) methods have become extremely promising and attractive. It has become extremely important to extract useful signals by decomposing various mixed signals through blind source
Ruiming Guo, Zhongqiang Luo, Mingchun Li
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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
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Grounding Grid Fault Diagnosis With Emphasis on Substation Electromagnetic Interference
IEEE Access, 2022 Grounding grid fault diagnosis is essential for the safe operation of a substation. However, the substation vicinity is highly electromagnetic. Therefore, the electromagnetic-based fault diagnosis is vulnerable to electromagnetic interference (EMI). This
Aamir Qamar +3 more
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Sensors, 2023 Joint blind source separation (JBSS) has wide applications in modeling latent structures across multiple related datasets. However, JBSS is computationally prohibitive with high-dimensional data, limiting the number of datasets that can be included in a ...
Mingyu Sun +6 more
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NeuroImage, 2020 The extraction of common and distinct biomedical signatures among different populations allows for a more detailed study of the group-specific as well as distinct information of different populations.
Qunfang Long +3 more
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Independent vector analysis (IVA): Multivariate approach for fMRI group study
NeuroImage, 2008 Independent component analysis (ICA) of fMRI data generates session/individual specific brain activation maps without a priori assumptions regarding the timing or pattern of the blood-oxygenation-level-dependent (BOLD) signal responses. However, because of a random permutation among output components, ICA does not offer a straightforward solution for ...
Jong-Hwan, Lee +3 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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Frontiers in Human Neuroscience, 2020 Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) can potentially enable people to non-invasively and directly communicate with others using brain activities.
Suguru Kanoga +3 more
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Comparison of IVA and GIG-ICA in Brain Functional Network Estimation Using fMRI Data
Frontiers in Neuroscience, 2017 Spatial group independent component analysis (GICA) methods decompose multiple-subject functional magnetic resonance imaging (fMRI) data into a linear mixture of spatially independent components (ICs), some of which are subsequently characterized as ...
Yuhui Du +10 more
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