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https://hdl.handle.net/2440/44883
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Type: | Conference paper |
Title: | Diagonally loaded normalised sample matrix inversion (LNSMI) for outlier-resistant adaptive filtering |
Author: | Abramovich, Yuri Spencer, Nicholas K. |
Citation: | IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP 2007, 15-20 April, 2007: vol. 3, pp. III-1105-III-1108 |
Publisher: | IEEE |
Issue Date: | 2007 |
ISBN: | 1424407281 |
Conference Name: | IEEE International Conference on Acoustics, Speech and Signal Processing (2007 : Honolulu, Hawaii) |
School/Discipline: | School of Electrical and Electronic Engineering |
Statement of Responsibility: | Abramovich, Y.I. and Spencer, N.K. |
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. |
Rights: | © Copyright 2007 IEEE – All Rights Reserved |
DOI: | 10.1109/ICASSP.2007.366877 |
Appears in Collections: | Electrical and Electronic Engineering publications |
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