The nonlinear PCA criterion in blind source separation: Relations with other approaches

DOI10.1016/S0925-2312(98)00046-0zbMath0911.68158OpenAlexW2070503991MaRDI QIDQ1272382

Petteri Pajunen, Juha Karhunen, Erkki Oja

Publication date: 21 December 1998

Published in: Neurocomputing (Search for Journal in Brave)

Full work available at URL: http://www.elsevier.com/locate/neucom

zbMATH Keywords

blind source separationprincipal component analysisadaptive EASI algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (5)

Using independent component for clustering of time series data ⋮ A comparison of block based Kalman filter and H-infinity algorithms for blind image separation ⋮ Adaptive Blind Separation with an Unknown Number of Sources ⋮ Abstract principal component analysis ⋮ A Generalized Contrast Function and Stability Analysis for Overdetermined Blind Separation of Instantaneous Mixtures

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