A Neural Network for PCA and Beyond

Authors:
Colin Fyfe
Affiliations:
Department of Computing and Information Systems, The University of Paisley. E-mail: fyfe0ci@paisley.ac.uk
Venue:
Neural Processing Letters
Year:
1997

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Abstract

Principal Component Analysis (PCA) has been implemented by several neuralmethods. We discuss a Network which has previously been shown to find thePrincipal Component subspace though not the actual Principal Componentsthemselves. By introducing a constraint to the learning rule (we do notallow the weights to become negative) we cause the same network to findthe actual Principal Components. We then use the network to identifyindividual independent sources when the signals from such sources are ORedtogether.