DocumentCode
871111
Title
Methods for chaotic signal estimation
Author
Kay, Steven ; Nagesha, Venkatesh
Author_Institution
Rhode Island Univ., Kingston, RI, USA
Volume
43
Issue
8
fYear
1995
fDate
8/1/1995 12:00:00 AM
Firstpage
2013
Lastpage
2016
Abstract
A dynamic programming algorithm and a suboptimal but computationally efficient method for estimation of a chaotic signal in white Gaussian noise are proposed. The nonlinear map is assumed known so that only the initial condition need be estimated. Computer simulations confirm that both approaches produce efficient estimates at high signal-to-noise ratios
Keywords
Gaussian noise; chaos; computational complexity; dynamic programming; interference (signal); maximum likelihood detection; maximum likelihood estimation; white noise; chaotic signal estimation; dynamic programming algorithm; high signal-to-noise ratios; initial condition; nonlinear map; suboptimal but computationally efficient method; white Gaussian noise; Chaos; Convergence; Electrons; Estimation; Gaussian noise; Heuristic algorithms; Radar; Signal processing algorithms; Smoothing methods; Taylor series;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.403367
Filename
403367
Link To Document