41 citations · 64 across the 5 of their papers we have counts for
9 papers
Independent Vector Extraction Constrained on Manifold of Half-Length Filters
Zbyněk Koldovský, Jaroslav Čmejla, Tülay Adalı +1
Independent Vector Analysis (IVA) is a popular extension of Independent Component Analysis (ICA) for joint separation of a set of instantaneous linear mixtures, with a direct appli…
Dynamic Independent Component Extraction with Blending Mixing Vector: Lower Bound on Mean Interference-to-Signal Ratio
Jaroslav Čmejla, Zbyněk Koldovský, Václav Kautský +1
This paper deals with dynamic Blind Source Extraction (BSE) from where the mixing parameters characterizing the position of a source of interest (SOI) are allowed to vary over time…
New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity Using Dictionary Learning
Fateme Ghayem, Hanlu Yang, Furkan Kantar +3
Independent component analysis (ICA) of multi-subject functional magnetic resonance imaging (fMRI) data has proven useful in providing a fully multivariate summary that can be used…
Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19
Zois Boukouvalas, Christine Mallinson, Evan Crothers +5
Social media has become an important communication channel during high impact events, such as the COVID-19 pandemic. As misinformation in social media can rapidly spread, creating…
Multidataset Independent Subspace Analysis with Application to Multimodal Fusion
Rogers F. Silva, Sergey M. Plis, Tulay Adali +2
In the last two decades, unsupervised latent variable models---blind source separation (BSS) especially---have enjoyed a strong reputation for the interpretable features they produ…
Tracing Network Evolution Using the PARAFAC2 Model
Marie Roald, Suchita Bhinge, Chunying Jia +3
Characterizing time-evolving networks is a challenging task, but it is crucial for understanding the dynamic behavior of complex systems such as the brain. For instance, how spatia…
Tensor-Based Fusion of EEG and FMRI to Understand Neurological Changes in Schizophrenia
Evrim Acar, Yuri Levin-Schwartz, Vince D. Calhoun +1
Neuroimaging modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) provide information about neurological functions in complementary spat…
Independent Component Analysis by Entropy Maximization with Kernels
Zois Boukouvalas, Rami Mowakeaa, Geng-Shen Fu +1
Independent component analysis (ICA) is the most popular method for blind source separation (BSS) with a diverse set of applications, such as biomedical signal processing, video an…
Enhancing ICA Performance by Exploiting Sparsity: Application to FMRI Analysis
Zois Boukouvalas, Yuri Levin-Schwartz, Tulay Adali
Independent component analysis (ICA) is a powerful method for blind source separation based on the assumption that sources are statistically independent. Though ICA has proven usef…