PCA is a linear technique and it is therefore not strictly applicable for handling industrial problems which exhibit significant non-linear behaviour. A novel ...
Nov 26, 2010 · A nonlinear principal component analysis methodology based upon the input-training neural network is proposed for the development of nonlinear ...
Principal component analysis has been used for the development of process performance monitoring schemes for both continuous and batch industrial processes.
PCA is a linear technique and it is therefore not strictly applicable for handling industrial problems which exhibit significant non-linear behaviour. A novel ...
A nonlinear principal component analysis methodology based upon the input-training neural network is proposed for the development of nonlinear process ...
A nonlinear principal component analysis methodology based upon the input-training neural network is proposed for the development of nonlinear process ...
A deep learning based nonlinear PCA method, referred to as deep PCA (DePCA), is proposed in this paper.
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Non-linear principal components analysis with application to process fault detection · Computer Science, Engineering. Int. J. Syst. Sci. · 2000.
Application of nonlinear PCA for fault detection in polymer extrusion ...
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Mar 29, 2011 · This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes.
Dec 31, 2011 · This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer ...