Adaptive Identification of Models Stabilizing Under Uncertainty

Author(s):  
Janislaw M. Skowronski
2003 ◽  
Vol 13 (04) ◽  
pp. 963-972 ◽  
Author(s):  
BAO-YUN WANG ◽  
T. W. S. CHOW ◽  
K. T. NG

In this article the identification of AR system driven by chaotic sequences is addressed. This problem emerges in chaotic communication system, in which chaos-modulated signal passes through a channel described as an AR system. Two adaptive algorithms are presented to tackle this problem. Compared with the existing algorithms such as MPSV and MNPE, the proposed algorithms have very low computational complexities and can be used to track the system parameters in a slowly time-variant environment. The obtained simulation results illustrate that the proposed scheme can offer a better estimation accuracy than the conventional typical method in the high SNR case.


2019 ◽  
Vol 47 (4) ◽  
pp. 691-698 ◽  
Author(s):  
Vladimir Ciganov

2004 ◽  
Vol 13 (3) ◽  
pp. 329-334 ◽  
Author(s):  
Wang Bao-Yun ◽  
Tommy W.S Chow ◽  
K.T Ng

2021 ◽  
Author(s):  
V.A. Simakhin ◽  
O.S. Cherepanov ◽  
Liudmila G. Shamanaeva

Sign in / Sign up

Export Citation Format

Share Document