Non-euclidean principal component analysis for matrices by Hebbian learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8467 LNAI, Issue PART 1, 2014, Pages 77-88

  Lange, Mandy ^a   Nebel, David ^a   Villmann, Thomas ^a  

^a UNIVERSITY OF APPLIED SCIENCES MITTWEIDA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BANACH SPACES; ITERATIVE METHODS; PRINCIPAL COMPONENT ANALYSIS; SOFT COMPUTING;

COMPLEXITY REDUCTION; COVARIANCE OPERATORS; HEBBIAN LEARNING; IMAGE DATA ANALYSIS; MATHEMATICAL THEORY; MATRIX CALCULATIONS; ONLINE LEARNING SCHEME; SEMI-INNER PRODUCTS;

MATHEMATICAL OPERATORS;

EID: 84902584827     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-07173-2_8     Document Type: Conference Paper

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