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Newton-type Methods in Array Processing

Selva, J. (2004) Newton-type Methods in Array Processing. IEEE Signal Processing Letters, 11 (2), pp. 104-107.

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Abstract

Despite their good features, Newton-type methods are not usually employed in array processing due to the lack of appropriate formulas for the first- and second-order differentials. One specific property of most array processing models is that each column of the signal matrix depends only on the corresponding element of one or more parameter vectors. In this letter, we exploit this property to derive compact expressions of the gradient, Hessian, and Hessian approximation of common maximum-likelihood (ML) cost functions, using a proper symbolic technique. Specifically, we study the conditional ML, row-correlated ML, and asymptotic ML cost functions.

Document Type:Article
Additional Information: LIDO-Berichtsjahr=2004,
Title:Newton-type Methods in Array Processing
Authors:
AuthorsInstitution or Email of Authors
Selva, J.UNSPECIFIED
Date:2004
Journal or Publication Title:IEEE Signal Processing Letters
Refereed publication:Yes
In ISI Web of Science:Yes
Volume:11
Page Range:pp. 104-107
Status:Published
Keywords:Newton-type, Array Processing
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W KN - Kommunikation/Navigation
DLR - Research area:Space
DLR - Program:W KN - Kommunikation/Navigation
DLR - Research theme (Project):UNSPECIFIED
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation
Deposited By: elib DLR-Beauftragter
Deposited On:16 Sep 2005
Last Modified:06 Jan 2010 21:32

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