Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Iterative solutions of min-max parameter estimation with bounded data uncertainties
 
conference paper

Iterative solutions of min-max parameter estimation with bounded data uncertainties

Sayed, Ali H.  
•
Garulli, Andrea
•
Chandrasekaran, Shivkumar
1997
IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP
IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP

This paper deals with the important problem of parameter estimation in the presence of bounded data uncertainties. Its recent closed-form solution in leads to more meaningful results than alternative methods (e.g., total least-squares and robust estimation), when a priori bounds about the uncertainties are available.The derivation in requires the computation of the SVD of thedata matrix and the determination of the unique positive root of a non-linear equation.This paper establishes the existence of a fundamental contraction mapping and uses this observation to propose an approximate recursive algorithm that avoids the need for explicit SVDs and for the solution of the nonlinear equation. Simulation results are included to demonstrate the good performance of the recursive scheme.

  • Details
  • Metrics
Type
conference paper
DOI
10.1109/ICASSP.1997.604635
Author(s)
Sayed, Ali H.  
Garulli, Andrea
Chandrasekaran, Shivkumar
Date Issued

1997

Published in
IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP
Volume

5

Start page

3561

End page

3564

Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
ASL  
Event nameEvent placeEvent date
IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP

Munich, Germany

April 21-24, 1997

Available on Infoscience
December 19, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/143266
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés