Denoising using local projective subspace methods

Neurocomputing

Volumn 69, Issue 13-15, 2006, Pages 1485-1501

  Gruber, P ^a   Stadlthanner, K ^a   Bohm M ^a   Theis, F J ^a   Lang, E W ^a   Tome A M ^b   Teixeira, A R ^b   Puntonet, C G ^c   Gorriz Saez J M ^c  

^a UNIVERSITY OF REGENSBURG   (Germany)

^b UNIVERSITY OF AVEIRO   (Portugal)

^c UNIVERSITY OF GRANADA   (Spain)

Author keywords

Delayed AMUSE; Local ICA; Projective subspace denoising embedding

Indexed keywords

ALGORITHMS; BLIND SOURCE SEPARATION; CORRELATION METHODS; ESTIMATION; NORMAL DISTRIBUTION;

AUTOCORRELATION; MULTI-DIMENSIONAL DATA; PROJECTIVE SUBSPACE DENOISING EMBEDDING; PROJECTIVE SUBSPACE METHODS;

SPURIOUS SIGNAL NOISE;

ALGORITHM; ANALYSIS OF VARIANCE; ARTICLE; CORRELATION ANALYSIS; IMAGE ANALYSIS; INDEPENDENT COMPONENT ANALYSIS; NOISE REDUCTION; NUCLEAR MAGNETIC RESONANCE; PRINCIPAL COMPONENT ANALYSIS; PRINCIPAL COORDINATE ANALYSIS; PRIORITY JOURNAL; PROTEIN ANALYSIS; SIGNAL DETECTION; STATISTICAL ANALYSIS;

EID: 33745200994     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2005.12.025     Document Type: Article

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