Title :
Multivariable nonlinear smoothers as an aid for identifying models from chaotic data
Author :
Mendes, Eduardo M A M
Author_Institution :
Departamento de Eletricidade, FUNREI, Sao Joao Del Rei, Brazil
Abstract :
Addresses the use of global multivariable smoothers for noise reduction of chaotic data so to as to aid the identification of dynamically valid models. Issues such as prediction, applicability of the proposed method and observed noise are briefly discussed.
Keywords :
autoregressive moving average processes; chaos; identification; iterative methods; noise; prediction theory; smoothing methods; chaotic data; dynamically valid models; linear identification; model identification; multivariable nonlinear smoothers; noise reduction; structure detection; Chaos; Filtering; Fractals; Noise reduction; Orbits; Phase detection; Phase noise; Smoothing methods; Solid modeling; State-space methods;
Conference_Titel :
American Control Conference, 2002. Proceedings of the 2002
Print_ISBN :
0-7803-7298-0
DOI :
10.1109/ACC.2002.1023140
