Warp convergence in conjugate gradient Wiener filters
2004 (English)In: 2004 IEEE Sensor Array and Multichannel Signal Processing Workshop: 18 - 21 July 2004, Barcelona, Spain, Piscataway, NJ: IEEE Communications Society, 2004, 109-113 p.Conference paper (Refereed)
In this work, we present interesting case studies that lead to new and deeper results on fast convergence of reduced-rank conjugate gradient (RRCG) Wiener filters (WF), for applications in communications and sensor array signal processing. We discover that for signal modes with a specially structured Gram matrix, which induces L groups of distinct eigenvalues in the data covariance matrix, a fast and predictable convergence, in at most L steps, can be achieved when the RRCG WF is used to detect, and/or to focus on, the desired signal mode. For such applications, given knowledge of the repeated eigenstructure of the Gram matrix of signal modes or of the measurement covariance matrix, a RRCG Wiener filter, of at most rank L, delivers the same performance as the full-rank Wiener filter. Typically L is much less than the rank of the Gram matrix.
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2004. 109-113 p.
Research subject Signal Processing
IdentifiersURN: urn:nbn:se:ltu:diva-37587DOI: 10.1109/SAM.2004.1502918Local ID: ba7ce430-f17c-11df-8b36-000ea68e967bISBN: 0-7803-8545-4 (print)OAI: oai:DiVA.org:ltu-37587DiVA: diva2:1011085
IEEE Sensor Array and Multichannel Signal Processing Workshop : 18/07/2004 - 21/07/2004
Upprättat; 2004; 20101116 (ysko)2016-10-032016-10-03Bibliographically approved