Mastering SIMULINK
Channel equalization for self-synchronizing chaotic systems
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03
Experimental evaluation of echo path modeling with chaotic codedspeech
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
An aperiodic phenomenon of the extended Kalman filter in filteringnoisy chaotic signals
IEEE Transactions on Signal Processing
Stabilizing controller design for uncertain nonlinear systems using fuzzy models
IEEE Transactions on Fuzzy Systems
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Together with the optimal linearization technique, a blind-channel equalization for the extended-Kalman-filter-based chaotic communication is 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. The proposed blind-channel equalization is formulated as a mixed nonlinear parameter and state estimation problem by an autoregressive (AR) model. The channel coefficients of a fading and multipath channel can be represented by an AR process. Then, an extended Kalman filter algorithm is utilized to reduce the effect of channel noise. By using the extended Kalman filter, the channel coefficients and the state of the system, which is the signal before going through the channel, can be estimated. The stability problem of the proposed blind-channel equalization is also addressed. Numerical examples and simulations are given to show the effectiveness and speed of convergence for the proposed methodology.