Abstract
Proposes a scheme based on orthogonal projection to identify a class of nonlinear auto-regressive, moving-average (NARMA) models. The scheme decouples the nonlinear and linear identification problems, and hence there are two steps. The first step extracts nonlinearities for each delay element within the model via conditional expectations. The second step evaluates dispersion functions to weight the nonlinear functions so that the cost is minimized. This paper focuses on the second step of the proposed scheme. The characteristics of the identification scheme are studied, and simulations are provided.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
