By Topic

Blind identifiability of third-order Volterra nonlinear systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hong-Zhou Tan ; Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada ; Aboulnasr, T.

A novel approach to estimate blindly the kernels of a Volterra nonlinear system up to the third order is proposed. The system is excited by an unobservable i.i.d. random sequence. Blind identifiability is achieved using second order statistics (SOS) rather than using higher order statistical (HOS) information to ensure lower complexity. Since the output of the Volterra system is linearly dependent upon its kernel parameters, conventional LMS or RLS algorithms can be used and consistent estimation of Volterra kernels can be achieved provided some conditions of persistent excitation (PE) are satisfied. Simulation demonstrated the ability of the proposed method to achieve a good estimation performance.

Published in:

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on  (Volume:6 )

Date of Conference:

6-10 April 2003