Results 21 to 30 of about 211 (100)

A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis

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, Ben Gabrielson, Mohammad Abu Baker Siddique Akhonda, Hanlu Yang, Francisco Laport, Vince Calhoun, Tülay Adali   +6 more
doaj   +1 more source

Independent Vector Analysis for Blind Deconvolving of Digital Modulated Communication Signals [PDF]

, 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, Chengjie Li, Ruiming Guo
core   +1 more source

Audio/Video Supervised Independent Vector Analysis through multimodal pilot dependent components [PDF]

, 2017
Independent Vector Analysis is a powerful tool for estimating the broadband acoustic transfer function between multiple sources and the microphones in the frequency domain. In this work, we consider an extended IVA model which adopts the concept of pilot
Mosayyebpour Saeed, Nesta Francesco, Koldovský Zbyněk, Paleček Karel   +3 more
core   +1 more source

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, Tariqullah Jan, Ruhul Amin Khalil, Ali Altalbe   +3 more
doaj   +1 more source

Independent Low-Rank Matrix Analysis-Based Automatic Artifact Reduction Technique Applied to Three BCI Paradigms

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, Takayuki Hoshino, Takayuki Hoshino, Hideki Asoh   +3 more
doaj   +1 more source

Data_Sheet_1_Comparative analysis of group information-guided independent component analysis and independent vector analysis for assessing brain functional network characteristics in autism spectrum disorder.docx [PDF]

, 2023
IntroductionGroup information-guided independent component analysis (GIG-ICA) and independent vector analysis (IVA) are two methods that improve estimation of subject-specific independent components in neuroimaging studies.
Bharat B. Biswal (8256636), Min Sheng (3992921), Benjamin Klugah-Brown (11521741), Junlin Jing (14610998), Shiyu Xia (14549684)   +4 more
core   +1 more source

Robust independent vector analysis based on exploiting phase continuity of the unmixing matrix [PDF]

, 2012
Independent vector analysis (IVA) is a recently proposed method to solve the permutation problem of frequency domain convolutive blind source separation (FD-CBSS).
Liang, Y, Chambers, JA, Yanfeng Liang, Jonathon A. Chambers, Naqvi, SM, Syed Mohsen Naqvi   +5 more
core   +3 more sources

Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI Data

Sensors, 2022
It is becoming increasingly common to collect multiple related neuroimaging datasets either from different modalities or from different tasks and conditions.
M. A. B. S. Akhonda, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali   +3 more
doaj   +1 more source

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, Andrew eMichael, Mathew eAnderson, Robyn eMiller, Tülay eAdalı, Vince D Calhoun, Vince D Calhoun   +6 more
doaj   +1 more source

Auxiliary-Function-Based Independent Vector Analysis Using Generalized Inter-Clique Dependence Source Models With Clique Variance Estimation

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