By Topic

Robust recursive spectral estimation based on an AR model excited by a t-distribution process by using QR decomposition algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sanubari, J. ; Dept. of Electron. Eng., Satya Wacana Univ., Salatiga, Indonesia ; Tokuda, K.

In this paper a new robust recursive, QR decomposition based, spectral estimation which is based on an AR model is proposed. The parallelism of the QR decomposition approach is used to facilitate the possibility for implementing the algorithm on an array processor architecture. The optimal coefficient of the AR model is selected by assuming that the excitation signal is a t-distribution with a degrees of freedom. When α=∞, we get the conventional QR decomposition RLS method. Simulation results show that, when the excitation signal is spiky, the obtained estimates using the proposed method with small α are more efficient, the standard deviation (SD) of the estimation results are smaller, and more accurate than that with large α and with Huber's estimator

Published in:

Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on  (Volume:4 )

Date of Conference:

9-12 Jun 1997