Together with the optimal linearization technique, an extended-Kalman-filter-based chaotic communication is first proposed in this paper. First, the optimal linearization technique is utilized to find the exact linear models of the chaotic system at operating states of interest. Then, an extended Kalman filter (EKF) algorithm is used to estimate both the parameters and states where the message is already embedded. By using the EKF together with the optimal linear model, the message can be recovered well at the receiver's end. Numerical examples and simulations are given to show the effectiveness of the proposed methodology.
|Number of pages||22|
|Journal||IMA Journal of Mathematical Control and Information|
|Publication status||Published - 2005 Mar 1|
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Control and Optimization
- Applied Mathematics