NDLI: Dynamic reconstruction of sea clutter using regularized REP networks

Content Provider	IEEE Xplore Digital Library
Author	Haykin, S. Puthusserypady, S. Yee, P.
Copyright Year	1998
Description	Author affiliation: Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada (Haykin, S.)
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.
Starting Page	19
Ending Page	23
File Size	501881
Page Count	5
File Format	PDF
ISBN	0780351487
ISSN	10586393
DOI	10.1109/ACSSC.1998.750821
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-11-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radial basis function networks Function approximation Predictive models Delay effects Chaos Noise robustness Sampling methods Trajectory
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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Dynamic reconstruction of sea clutter using regularized REP networks