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A "nonnegative PCA" algorithm for independent component analysis

Plumbley, MD and Oja, E (2004) A "nonnegative PCA" algorithm for independent component analysis IEEE TRANSACTIONS ON NEURAL NETWORKS, 15 (1). pp. 66-76.

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Item Type: Article
Authors :
NameEmailORCID
Plumbley, MDm.plumbley@surrey.ac.ukUNSPECIFIED
Oja, EUNSPECIFIEDUNSPECIFIED
Date : 1 January 2004
Identification Number : 10.1109/TNN.2003.820672
Uncontrolled Keywords : Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Hardware & Architecture, Computer Science, Theory & Methods, Engineering, Electrical & Electronic, Computer Science, Engineering, independent component analysis (ICA), nonlinear principal component analysis (nonlinear PCA), nonnegative matrix factorization, subspace learning rule, MATRIX FACTORIZATION, SOURCE SEPARATION, CONSTRAINTS, CONVERGENCE, MODEL
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 13:35
Last Modified : 17 May 2017 15:11
URI: http://epubs.surrey.ac.uk/id/eprint/839751

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