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. © 1995 IEE
This work presents novel techniques for state estimation of nonlinear stochastic systems, specifical...
This work presents novel techniques for state estimation of nonlinear stochastic systems, specifical...
We derive the Cramer-Rao Lower Bound (CRLB) for the estimation of initial conditions of noise-embedd...
A dynamic programming algorithm and a suboptimal but computationally efficient method for estimation...
The subject of parameter estimation in linear signals embedded in white Gaussian noise has been exte...
Abstract:- This paper addresses the problem of noise reduction for chaotic signals. The existing app...
Chaotic signals are potentially attractive in engineering applications, most of which require an acc...
We present a noise-filtering scheme which works on a chaotic signal containing a certain level of no...
This work presents novel techniques for state estimation of nonlinear stochastic systems, especially...
This work presents novel techniques for state estimation of nonlinear stochastic systems, especially...
In this paper, the additive white noise was filtered from chaotic signals obtained by Logistic map b...
Nonlinear dynamical systems with chaotic behaviour generate noise-like broadband signals by determin...
The performance of the maximum likelihood estimator for a 1-D chaotic signal in white Gaussian noise...
This paper considers the generation of chaotic signals and selected application fields with emphasis...
This book provides a systematic review of the fundamental theory of signal reconstruction and the pr...
This work presents novel techniques for state estimation of nonlinear stochastic systems, specifical...
This work presents novel techniques for state estimation of nonlinear stochastic systems, specifical...
We derive the Cramer-Rao Lower Bound (CRLB) for the estimation of initial conditions of noise-embedd...
A dynamic programming algorithm and a suboptimal but computationally efficient method for estimation...
The subject of parameter estimation in linear signals embedded in white Gaussian noise has been exte...
Abstract:- This paper addresses the problem of noise reduction for chaotic signals. The existing app...
Chaotic signals are potentially attractive in engineering applications, most of which require an acc...
We present a noise-filtering scheme which works on a chaotic signal containing a certain level of no...
This work presents novel techniques for state estimation of nonlinear stochastic systems, especially...
This work presents novel techniques for state estimation of nonlinear stochastic systems, especially...
In this paper, the additive white noise was filtered from chaotic signals obtained by Logistic map b...
Nonlinear dynamical systems with chaotic behaviour generate noise-like broadband signals by determin...
The performance of the maximum likelihood estimator for a 1-D chaotic signal in white Gaussian noise...
This paper considers the generation of chaotic signals and selected application fields with emphasis...
This book provides a systematic review of the fundamental theory of signal reconstruction and the pr...
This work presents novel techniques for state estimation of nonlinear stochastic systems, specifical...
This work presents novel techniques for state estimation of nonlinear stochastic systems, specifical...
We derive the Cramer-Rao Lower Bound (CRLB) for the estimation of initial conditions of noise-embedd...
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