A fast incremental kernel principal component analysis for online feature extraction

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

Volumn 6230 LNAI, Issue , 2010, Pages 487-497

  Ozawa, Seiichi ^a   Takeuchi, Yohei ^a   Abe, Shigeo ^a  

^a KOBE UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ACCURACY; EIGENVALUE DECOMPOSITION; EIGENVALUE PROBLEM; EIGENVALUES; EIGENVECTORS; FEATURE SPACE; HIGH-DIMENSIONAL FEATURE SPACE; INCREMENTAL LEARNING; KERNEL PRINCIPAL COMPONENT ANALYSIS; LEARNING PHASE; LEARNING PHASIS; LEARNING TIME; MATRIX SIZE; NONLINEAR FEATURE EXTRACTION METHOD; ONLINE FEATURE EXTRACTION;

ARTIFICIAL INTELLIGENCE; EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; SWITCHING SYSTEMS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 78049293320     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15246-7_45     Document Type: Conference Paper

References (11)

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