Title :
Entropy analysis applied to NFIR models
Author :
Ludwig, Oswaldo ; Lima, A. C De Castro ; Schnitman, Leizer ; De Souza, J. A M Felippe
Author_Institution :
Univ. Fed. da Bahia, Salvador, Brazil
Abstract :
This present work has been developed in view of a research project that aims a mapping process between infrared images and thermo pair sensors readings in diesel motors by the use of artificial neural network. The consistence analysis of a set of examples used in the supervised training of artificial neural networks is presented. The proposed approach is based on the entropy analysis of both input and output data. The principal component analysis method is applied to avoid redundant information that can lead to an entropy level overestimation.
Keywords :
FIR filters; diesel engines; entropy; identification; infrared imaging; learning (artificial intelligence); neural nets; nonlinear filters; principal component analysis; regression analysis; NFIR models; artificial neural networks; consistence analysis; diesel motors; entropy analysis; infrared images; mapping process; nonlinear finite impulse response; principal component analysis; supervised training; thermo pair sensors readings; Artificial neural networks; Covariance matrix; Entropy; Infrared image sensors; Multilayer perceptrons; Nonlinear equations; Principal component analysis; System identification; Thermal sensors; Vectors;
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2005.1470153
