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Avtorstvo: Vlado STANKOVSKI // 1.08 Objavljeno predavanje na znanstveni konferenci
Leto: 1994
Citat: STANKOVSKI, Vlado, FEFER, Dušan. Prediction and system identification by using neural nets. V: SOLINA, Franc (ur.), ZAJC, Baldomir (ur.). Zbornik tretje Elektrotehniške in računalniške konference ERK '94, 26. - 28. september 1994, Portorož, Slovenija. Ljubljana: Slovenska sekcija IEEE, 1994, zv. A, str. 527-530, graf. prikazi.
Povzetek: We consider the problem of prediction of time series exhibiting broadband spectrum which arise from the intrinsic nonlinear dynamics of the system that is observed. The time series are embbeded in a reconstructed phase space which captures the attractor on which the system evolves. The predictor of future points in the phase space is a back-propagation neural network especially designed for this purpose. We trained the neural network with various time series, both sampled from a physical system or computed by integration of differential equations. We examine the prediction results by computing the relative prediction error (Rer) and the correlation coefficient between the real and the predicted time series. We show that by computing the correlation coefficient it is possible to distinquish the deterministic and chaotic from the random time series. This measure can further be used in the process of identification of the observed system. [COBISS.SI-ID 637268]
Tipologija: 1.08 Objavljeno predavanje na znanstveni konferenci
COBISS ID 637268 Polni zapis iz sistema COBISS
Vpisal 2009/06/10 11:56