Practical techniques for rapid and reliable real-time adaptive filtering

Simplicity, flexibility, and reliability are three important aspects of practical adaptive filtering systems. In this work, two techniques are investigated which address these issues. First, a new class of data-reusing LMS algorithms is explored. These algorithms are seen, through extensive simulation examples, to have superior convergence rate and Mean-Squared Error performance over the Data-Reusing LMS algorithm at the same computational cost. A geometric framework which aids in the presentation of the new class of algorithms is developed. This framework also allows a more complete understanding of three existing LMS-type algorithms, as well as allows the proof of several important convergence rate properties which relate the three algorithms.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Schnaufer, Bernard A.

Contributors dc:contributor

• Jenkins, W. Kenneth

• Engineering, Electronics and Electrical

Statement dc:rights

• Copyright 1995 Schnaufer, Bernard A.

Language dc:language

eng

Identifier

AAI9522170
(UMI)AAI9522170

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/20661