Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/44883
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Abramovich, Yuri | en |
dc.contributor.author | Spencer, Nicholas K. | en |
dc.date.issued | 2007 | en |
dc.identifier.citation | IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP 2007, 15-20 April, 2007: vol. 3, pp. III-1105-III-1108 | en |
dc.identifier.isbn | 1424407281 | en |
dc.identifier.uri | http://hdl.handle.net/2440/44883 | - |
dc.description.abstract | Instead of a "hard" decision on ignoring "outlier" training samples in constructing the covariance matrix estimate, we propose a "softer" method that reduces the impact of such abnormal data samples on adaptive filter performance. Specifically, we introduce a diagonally loaded covariance matrix estimate that is normalised by a generalised inner product (GIP), which is more robust against outliers. We demonstrate the efficiency of this technique on high-frequency (HF) over-the-horizon radar (OTHR) data. | en |
dc.description.statementofresponsibility | Abramovich, Y.I. and Spencer, N.K. | en |
dc.language.iso | en | en |
dc.publisher | IEEE | en |
dc.rights | © Copyright 2007 IEEE – All Rights Reserved | en |
dc.title | Diagonally loaded normalised sample matrix inversion (LNSMI) for outlier-resistant adaptive filtering | en |
dc.type | Conference paper | en |
dc.contributor.school | School of Electrical and Electronic Engineering | en |
dc.contributor.conference | IEEE International Conference on Acoustics, Speech and Signal Processing (2007 : Honolulu, Hawaii) | en |
dc.identifier.doi | 10.1109/ICASSP.2007.366877 | en |
Appears in Collections: | Electrical and Electronic Engineering publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.