The aim of this research work is to present a detailed theoretical analysis of the one-unit learning rule based on the rigid-bodies learning theory, specialized for 6rst principal/independent component analysis. The adaptation equations are regarded as generators of weight-8ows on a structuredparameters space; the stationary points of the learning equations are determined andtheir stability is proven through a suitable Lyapunov function. The neuron is also excited with both synthetic andreal-worldsignals in order to numerically investigate its behavior, and eddy-current-signal processing is carried out as an application of the developed independent component analysis algorithm to non-destructive evaluation of metallic objects.
One-Unit `Rigid-Bodies' Learning Rule for Principal/Independent Component Analysis with Application to ECT-NDE Signal Processing
FIORI, Simone;BURRASCANO, Pietro
2004
Abstract
The aim of this research work is to present a detailed theoretical analysis of the one-unit learning rule based on the rigid-bodies learning theory, specialized for 6rst principal/independent component analysis. The adaptation equations are regarded as generators of weight-8ows on a structuredparameters space; the stationary points of the learning equations are determined andtheir stability is proven through a suitable Lyapunov function. The neuron is also excited with both synthetic andreal-worldsignals in order to numerically investigate its behavior, and eddy-current-signal processing is carried out as an application of the developed independent component analysis algorithm to non-destructive evaluation of metallic objects.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
