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A hierarchical approach to noise-adaptive estimation
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
2010 (engelsk)Inngår i: 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Piscataway, NJ: IEEE Communications Society, 2010, s. 161-164Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper presents a noise-adaptive estimator for the linear model. The strategy is based on a hierarchical approach where in each step, a decreasing number of unbiased estimates for the parameter of interest is produced. In this way, the complexity is greatly reduced compared to standard estimators, like the adaptive maximum likelihood (AML) estimator. Also, since the method combines solutions to sub-problems of smaller dimensionality, the required size of the noise training data set is also reduced. As a result, the derived scheme performs better than AML for small sample support. The results are verified by simulations and show that the derived scheme is a very appropriate choice for a large class of problems with high dimensionality.

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE Communications Society, 2010. s. 161-164
Serie
Sensor Array and Multichannel Signal Processing. I E E E Works, ISSN 1551-2282
HSV kategori
Forskningsprogram
Signalbehandling
Identifikatorer
URN: urn:nbn:se:ltu:diva-39050DOI: 10.1109/SAM.2010.5606722Scopus ID: 2-s2.0-78650120536Lokal ID: da418110-efd6-11df-8b36-000ea68e967bISBN: 978-1-4244-9395-1 (tryckt)ISBN: 978-1-4244-9395-1 (digital)OAI: oai:DiVA.org:ltu-39050DiVA, id: diva2:1012558
Konferanse
IEEE Sensor Array and Multichannel Signal Processing Workshop : 04/10/2010 - 07/10/2010
Merknad
Godkänd; 2010; 20101114 (ysko)Tilgjengelig fra: 2016-10-03 Laget: 2016-10-03 Sist oppdatert: 2018-07-10bibliografisk kontrollert

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