Title :
A general efficient method for chaotic signal estimation
Author :
Cong, Ling ; Xiaofu, Wu ; Songgeng, Sun
Author_Institution :
Nanjing Inst. of Commun. Eng., China
fDate :
5/1/1999 12:00:00 AM
Abstract :
This article presents a general, computationally efficient method for chaotic signal estimation based on the connection between the symbolic sequence and the initial condition of a chaotic system. The performance of the method in white Gaussian noise is evaluated. The new method is asymptotically unbiased and attains the Cramer-Rao lower bound at high signal-to-noise ratios
Keywords :
Gaussian noise; chaos; convergence of numerical methods; parameter estimation; sequences; signal processing; white noise; Cramer-Rao lower bound; SNR; asymptotically unbiased method; chaotic signal estimation; chaotic system; convergence rate; fixed-lag smoothing algorithm; general computationally efficient method; high signal-to-noise ratios; initial condition; performance; symbolic sequence; white Gaussian noise; Adaptive filters; Chaos; Convergence; Estimation; Finite impulse response filter; Gaussian noise; Least squares approximation; Signal analysis; Signal processing algorithms; Testing;
Journal_Title :
Signal Processing, IEEE Transactions on
