A globally convergent modified OE IIR adaptive filter for sufficient modeling

TitleA globally convergent modified OE IIR adaptive filter for sufficient modeling
Publication TypeConference Paper
Year of Publication1998
AuthorsMayyas, K., and T. Aboulnasr
Conference NameAcoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Pagination1729 -1732 vol.3
Date Publishedmay.
Keywordsadaptive filters, adaptive signal processing, adaptive update scheme, convergence of numerical methods, error analysis, error surface, filtering theory, globally convergent modified filter, IIR filters, input signal whitening, least mean square, least mean squares methods, LMS, OE IIR adaptive filter, sufficient modeling

A modification to the OE IIR system structure is proposed to ensure global convergence for sufficient modeling of the unknown system. The proposed structure is effectively equivalent to whitening the input signal before being applied to the original OE setup. This guarantees the unimodality of the error surface for sufficient modeling. An adaptive update scheme for the new structure is derived based on the least mean square (LMS) technique. Examples are provided to demonstrate the effectiveness of the proposed structure under different conditions


a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2021 The University of British Columbia