Skip to main content

Transform domain adaptive filtering algorithm via modified power estimator

Kim, D.I., De Wilde, Philippe (2000) Transform domain adaptive filtering algorithm via modified power estimator. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E83-A (4). pp. 764-770. ISSN 0916-8508. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:93387)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://search.ieice.org/bin/summary.php?id=e83-a_...

Abstract

This letter analyses the convergence behaviour of the transform domain least mean square (TDLMS) adaptive filtering algorithm which is based on a well known interpretation of the variable stepsize algorithm. With this interpretation, the analysis is considerably simplified. The time varying stepsize is implemented by the modified power estimator to redistribute the spread power after transformation. The main contribution of this letter is the statistical performance analysis in terms of mean and mean squared error of the weight error vector and the decorrelation property of the TDLMS is presented by the lower and upper bound of eigenvalue spread ratio. The theoretical analysis results are validated by Monte Carlo simulation.

Item Type: Article
Uncontrolled keywords: Transform domain adaptive filter
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Philippe De Wilde
Date Deposited: 03 Jan 2023 16:18 UTC
Last Modified: 04 Jan 2023 14:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/93387 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.