Application of the sequential matrix diagonalization algorithm to high-dimensional functional MRI data

DOI10.1007/s00180-019-00925-8zbMath1482.62006OpenAlexW2979429784WikidataQ127102794 ScholiaQ127102794MaRDI QIDQ782634

Soydan Redif, Manuel Carcenac

Publication date: 28 July 2020

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-019-00925-8

zbMATH Keywords

functional magnetic resonance imagingMIMO convolutionpolynomial eigenvalue decompositionsequential matrix diagonalizationsparse polynomial matrix

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Functional data analysis (62R10) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (1)

Supervised classification of curves via a combined use of functional data analysis and tree-based methods

Uses Software

• CUDA
• JDQR
• FEAST
• MKL
• JDQZ

Cites Work

• Fast projection methods for minimal design problems in linear system theory
• Independent component analysis, a new concept?
• Independent component analysis for tensor-valued data
• Templates for the Solution of Algebraic Eigenvalue Problems
• An EVD Algorithm for Para-Hermitian Polynomial Matrices
• Sequential Matrix Diagonalization Algorithms for Polynomial EVD of Parahermitian Matrices
• On the Existence and Uniqueness of the Eigenvalue Decomposition of a Parahermitian Matrix
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