A fast recursive least-squares adaptive nonlinear filter

Update item information
Publication Type Journal Article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Mathews, V. John
Title A fast recursive least-squares adaptive nonlinear filter
Date 1988
Description This paper presents a fast, recursive least-squares (RLS) adaptive nonlinear filter. The nonlinearity in the system is modeled using the Hammerstein model, which consists of a memoryless polynomial nonlinearity followed by a finite impulse response linear system. The complexity of our method is about 3NP2+7NP+N+10P2+6P multiplications per iteration and is substantially lower than the computational complexities of fast RLS algorithms that are direct extensions of RLS adaptive linear filters to the nonlinear case.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 156
Last Page 160
Language eng
Bibliographic Citation Mathews, V. J. (1988). A fast recursive least-squares adaptive nonlinear filter. Proc. 21st Annual Asilomar Conf. Signals, Systems and Computers, 156-60. November.
Rights Management (c)1988 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 651,938 bytes
Identifier ir-main,15132
ARK ark:/87278/s6pg29bh
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2021-05-06
ID 707087
Reference URL https://collections.lib.utah.edu/ark:/87278/s6pg29bh
Back to Search Results