T
Tulay Adali
Researcher at University of Maryland, Baltimore County
Publications - 466
Citations - 22805
Tulay Adali is an academic researcher from University of Maryland, Baltimore County. The author has contributed to research in topics: Independent component analysis & Blind signal separation. The author has an hindex of 64, co-authored 429 publications receiving 20040 citations. Previous affiliations of Tulay Adali include Johns Hopkins University & University of Baltimore.
Papers
More filters
Proceedings ArticleDOI
Non-orthogonal constrained independent vector analysis: Application to data fusion
Suchita Bhinge,Qunfang Long,Yuri Levin-Schwartz,Zois Boukouvalas,Vince D. Calhoun,Tulay Adali +5 more
TL;DR: This paper proposes a general formulation for non-orthogonal constrained IVA (C-IVA) framework that can incorporate prior information about either the sources or the mixing coefficients into the IVA cost function.
Posted ContentDOI
Parallel Group ICA + ICA: Joint Estimation of Linked Functional Network Variability and Structural Covariation with Application to Schizophrenia
Shile Qi,Jing Sui,Jing Sui,Jiayu Chen,Jingyu Liu,Rongtao Jiang,Rogers F. Silva,Armin Iraji,Eswar Damaraju,Mustafa Salman,Dongdong Lin,Zening Fu,Dongmei Zhi,Jessica A. Turner,Juan R. Bustillo,Judith M. Ford,Daniel H. Mathalon,James T. Voyvodic,Sarah McEwen,Adrian Preda,Aysenil Belger,Steven G. Potkin,Bryon A. Mueller,Tulay Adali,Vince D. Calhoun,Vince D. Calhoun +25 more
TL;DR: Results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.
Journal ArticleDOI
Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia
TL;DR: The findings demonstrate that structural phase and magnitude images can naturally and efficiently summarize the associated relationship between gray and white matter and identify tissue distribution abnormalities in schizophrenia.
Proceedings ArticleDOI
Efficient learning of standard finite normal mixtures for image quantification
Yue Wang,Tulay Adali +1 more
TL;DR: It is shown that by incorporating learning rate adaptation in a sequential mode, PSOM achieves fast convergence and has efficient learning capabilities which make it very attractive for many practical image quantification applications; such as unsupervised image segmentation and diagnosis by medical images.
Proceedings ArticleDOI
Channel equalization with perceptrons: an information-theoretic approach
Tulay Adali,M.K. Sonmez +1 more
TL;DR: The adaptive channel equalization is formulated as a conditional probability distribution learning problem and the resulting algorithm successfully equalizes multipath channels via maximum partial likelihood estimation of logistic models.