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Directional Clustering through Matrix Factorization Experiments

Directional Clustering through Matrix Factorization Experiments
Directional Clustering through Matrix Factorization Experiments
These data files and matlab scripts allow the user to recreate the numerical experiments in the paper Thomas Blumensath, "Directional Clustering through Matrix Factorisation," to appear in IEEE Transactions on Neural Networks and Learning Systems. Funded by EPSRC (EP/J005444/1; Advanced FMRI acquisition, reconstruction and signal processing for dynamic brain network imaging; 2012 to 2015).
University of Southampton
Blumensath, Thomas
470d9055-0373-457e-bf80-4389f8ec4ead
Blumensath, Thomas
470d9055-0373-457e-bf80-4389f8ec4ead

Blumensath, Thomas (2015) Directional Clustering through Matrix Factorization Experiments. University of Southampton doi:10.5258/SOTON/384519 [Dataset]

Record type: Dataset

Abstract

These data files and matlab scripts allow the user to recreate the numerical experiments in the paper Thomas Blumensath, "Directional Clustering through Matrix Factorisation," to appear in IEEE Transactions on Neural Networks and Learning Systems. Funded by EPSRC (EP/J005444/1; Advanced FMRI acquisition, reconstruction and signal processing for dynamic brain network imaging; 2012 to 2015).

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README.txt - Text
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Archive
ClusteringPaperCode.zip - Dataset
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More information

Published date: 2015
Organisations: Inst. Sound & Vibration Research
Projects:
Constrained low rank matrix recovery: from efficient algorithms to brain network imaging
Funded by: UNSPECIFIED (EP/K037102/1)
4 January 2014 to 31 December 2014
Advanced FMRI acquisition, reconstruction and signal processing for dynamic brain network imaging
Funded by: UNSPECIFIED (EP/J005444/1 )
February 2012 to August 2015

Identifiers

Local EPrints ID: 384519
URI: http://eprints.soton.ac.uk/id/eprint/384519
PURE UUID: d64e42f2-3218-4d3e-b62c-cc315cb6c253
ORCID for Thomas Blumensath: ORCID iD orcid.org/0000-0002-7489-265X

Catalogue record

Date deposited: 30 Nov 2015 15:46
Last modified: 05 Nov 2023 02:44

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