Title :
Dynamic reconstruction of sea clutter using regularized REP networks
Author :
Haykin, Simon ; Puthusserypady, Sadasivan ; Yee, Paul
Author_Institution :
Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada
Abstract :
We demonstrate the dynamic reconstruction of sea clutter time series using a regularized radial basis function (RBF) network. The dynamic invariants, namely, correlation dimension, Lyapunov exponents and the Kaplan-Yorke dimension of the actual and the reconstructed time series are compared to confirm the goodness of fit of the RBF model to the actual clutter data. A detailed statistical analysis of the horizon of predictability is presented to show the model´s ability to capture the underlying dynamics of sea clutter. These convincing results show that the RBF model is capable of approximating the dynamics of sea clutter process in a convincing manner.
Keywords :
Lyapunov methods; approximation theory; correlation methods; radar clutter; radar computing; radial basis function networks; signal reconstruction; statistical analysis; time series; Kaplan-Yorke dimension; Lyapunov exponents; RBF model; actual time series; correlation dimension; dynamic invariants; dynamic reconstruction; horizon of predictability; reconstructed time series; regularized REP networks; regularized radial basis function network; sea clutter; statistical analysis; Chaos; Delay effects; Function approximation; Noise robustness; Predictive models; Radial basis function networks; Sampling methods; Trajectory;
Conference_Titel :
Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-5148-7
DOI :
10.1109/ACSSC.1998.750821
