DocumentCode :
1527273
Title :
Performance evaluation of EKF-based chaotic synchronization
Author :
Leung, Henry ; Zhu, Zhiwen
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Volume :
48
Issue :
9
fYear :
2001
fDate :
9/1/2001 12:00:00 AM
Firstpage :
1118
Lastpage :
1125
Abstract :
The performance of chaotic synchronization based on the extended Kalman filter (EKF) is investigated here. We first establish the relationship between the EKF-based synchronization method and two conventional synchronization method, drive-response and unidirectionally coupled methods. The performance of the EKF-based synchronization method in the presence of channel noise is then derived in terms of mean square error (MSE) between the drive and response systems for one-dimensional discrete-time systems. Compared with the optimal coupled synchronization method, the EKF-based synchronization method is shown to have the same MSE performance for chaotic systems with gradient square independent of the system states (Type-I systems). For chaotic systems with state-dependent gradient square (Type-II systems), the EKF-based method is found to have a smaller MSE. The averaged Cramer-Rao lower bound (CRLB) is introduced here as a performance measure. It is shown that the EKF-based method approaches the averaged CRLB for both Type-I and Type-II systems when noise level is low. Our theoretical results are verified by using Monte Carlo simulation on three popular one-dimensional chaotic systems
Keywords :
Kalman filters; Monte Carlo methods; chaos; discrete time filters; mean square error methods; nonlinear filters; synchronisation; Cramer-Rao lower bound; Monte Carlo simulation; Type-I system; Type-II system; channel noise; chaotic synchronization; drive response method; extended Kalman filter; mean square error; nonlinear filtering; one-dimensional discrete-time system; performance evaluation; unidirectionally coupled method; Application software; Chaos; Chaotic communication; Drives; Filtering; Kalman filters; Mean square error methods; Motion control; Noise level; State feedback;
fLanguage :
English
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7122
Type :
jour
DOI :
10.1109/81.948440
Filename :
948440
Link To Document :
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