Model Breaking Detection Using Independent Component Classifier

Abstract

This paper presents a neural architecture for model breaking detection in real world conditions. This technique use an Independent Component Classiier 1] for detection of unexpected or unknown events in noisy and varying environment. This method is based on subspace classier 2] and Independant Component Analysis 3]. A feed-forward neural network adapts… (More)
DOI: 10.1007/BFb0020213

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