By Topic

An Efficient Line-Search Algorithm for Unbiased Recursive Least-Squares Filtering With Noisy Inputs

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)
ByungHoon Kang ; Dept. of Electr. Eng., Pohang Univ. of Sci. & Technol., Pohang, South Korea ; PooGyeon Park

This letter proposes a new algorithm for efficiently finding an unbiased RLS estimate of FIR models with noisy inputs. The unbiased estimate is obtained without knowing any a priori information via a new cost. Furthermore, to reduce computational complexity, the estimate is updated along the current input-vector direction and the corresponding gain is efficiently computed. In addition, to increase the convergence rate, the algorithm is extended to update the estimate along not only current but also past input-vector directions. Simulation results show that the proposed algorithm exhibits a fast convergence rate and an enhanced tracking performance with noisy correlated inputs.

Published in:

Signal Processing Letters, IEEE  (Volume:20 ,  Issue: 7 )