Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Performance of LMS algorithm as a function of input signal pole loci

Performance of LMS algorithm as a function of input signal pole loci

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Add to cart
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)
Add to cart

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

© The Institution of Electrical Engineers
Published

The degree to which the performance of the adaptive LMS transversal filter depends on the ratio of the extreme eigen-values of the input autocorrelation matrix is investigated. Subsequently, performance is related to the spectral properties of the input signal via a study of the relationship between the eigenvalues and the loci of the poles characterising the input signal.

Inspec keywords: least squares approximations; filtering and prediction theory; digital filters

Other keywords: input signal pole loci; performance; spectral properties; adaptive LMS transversal filter; eigenvalues; digital filters; LMS algorithm; input autocorrelation matrix

Subjects: Interpolation and function approximation (numerical analysis); Digital filters; Signal processing and detection; Interpolation and function approximation (numerical analysis); Digital filters; Information theory

References

    1. 1)
      • B. Widrow , R. Kalman , N. Declaris . (1970) Adaptive filters, Aspects of network and system theory.
    2. 2)
      • B. Widrow , J.M. McCool , M.G. Larimore , C.R. Johnson . Stationary and nonstationary learning characteristics of the LMS adaptive filters. Proc. IEEE , 1151 - 1162
http://iet.metastore.ingenta.com/content/journals/10.1049/el_19870341
Loading

Related content

content/journals/10.1049/el_19870341
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address