Adaptive signal processing : next generation solutions /

Por Adali, Tülay., Haykin, Simon S.
Publicado em c201

Independent component analysis and signal separation : 8th International Conference, ICA 2009, Paraty, Brazil, March 15 - 18, 2009 proceedings /

Por ICA 2009, Adali, Tülay.
Publicado em c200

Independent component analysis and signal separation 8th International Conference, ICA 2009, Paraty, Brazil, March 15 - 18, 2009 : proceedings /

Por ICA 2009, Adali, Tulay.
Publicado em 2009

Feature-Based Fusion of Medical Imaging Data

Por Calhoun, Vince D., Adalı, Tulay
Publicado em 2008

Multi-subject Independent Component Analysis of fMRI: A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery

Por Calhoun, Vince D, Adalı, Tülay
Publicado no IEEE Rev Biomed Eng (2012)

Performance of Blind Source Separation Algorithms for FMRI Analysis using a Group ICA Method

Por Correa, Nicolle, Adali, Tülay, Calhoun, Vince D.
Publicado em 2006

A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data

Por Calhoun, Vince D., Liu, Jingyu, Adalı, Tülay
Publicado em 2008

A window‐less approach for capturing time‐varying connectivity in fMRI data reveals the presence of states with variable rates of change

Por Yaesoubi, Maziar, Adalı, Tülay, Calhoun, Vince D.
Publicado no Hum Brain Mapp (2018)

A Feature-Selective Independent Component Analysis Method for Functional MRI

Por Li, Yi-Ou, Adalı, Tülay, Calhoun, Vince D.
Publicado em 2007

Automatic Bayesian classification of healthy controls, bipolar disorder and schizophrenia using intrinsic connectivity maps from fMRI data

Por Arribas, Juan I., Calhoun, Vince D., Adalı, Tülay
Publicado em 2010

Phase Ambiguity Correction and Visualization Techniques for Complex-Valued ICA of Group fMRI Data

Por Rodriguez, Pedro A., Calhoun, Vince D., Adalı, Tülay
Publicado em 2012

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

Por Adali, Tülay, Levin-Schwartz, Yuri, Calhoun, Vince D.
Publicado no Proc IEEE Inst Electr Electron Eng (2015)

Quantifying the Interaction and Contribution of Multiple Datasets in Fusion: Application to the Detection of Schizophrenia

Por Levin-Schwartz, Yuri, Calhoun, Vince D., Adalı, Tülay
Publicado no IEEE Trans Med Imaging (2017)

A Method to Compare the Discriminatory Power of Data-driven Methods: Application to ICA and IVA

Por Levin-Schwartz, Yuri, Calhoun, Vince D., Adali, Tülay
Publicado no J Neurosci Methods (2018)

Estimating the number of independent components for functional magnetic resonance imaging data

Por Li, Yi‐Ou, Adalı, Tülay, Calhoun, Vince D.
Publicado no Hum Brain Mapp (2007)

A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data

Por Sui, Jing, Adali, Tülay, Yu, Qingbao, Calhoun, Vince D.
Publicado em 2011

The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery

Por Calhoun, Vince D., Miller, Robyn, Pearlson, Godfrey, Adalı, Tulay
Publicado no Neuron (2014)

Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis

Por Ma, Sai, Calhoun, Vince D., Phlypo, Ronald, Adalı, Tülay
Publicado no Neuroimage (2014)

Spatial Dynamic Functional Connectivity Analysis Identifies Distinctive Biomarkers in Schizophrenia

Por Bhinge, Suchita, Long, Qunfang, Calhoun, Vince D., Adali, Tülay
Publicado no Front Neurosci (2019)

ICA and IVA for Data Fusion: An Overview and a New Approach Based on Disjoint Subspaces

Por Adali, Tulay, Akhonda, M.A.B.S., Calhoun, Vince D.
Publicado no IEEE Sens Lett (2018)