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Eigendecomposition versus singular value decomposition in adaptive array signal processing

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10.1016/0165-1684(91)90037-J
 
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hdl:2117/97154

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Duarte Ortigueira, Manuel
Lagunas Hernandez, Miguel A.Més informacióMés informació
Document typeArticle
Defense date1991-10
Rights accessRestricted access - publisher's policy
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Two important questions in array signal processing are addressed in this paper: the data matrix versus autocorrelation matrix alternative and the recursive implementation of subspace DOA methods. The discussion of the first question is done in face of the proposed class of recursive algorithms. These new algorithms are easily implementable and have a high degree of parallelism that is suitable for on-line implementations. Algorithms for recursive implementation of the eigendecomposition (ED) of the autocorrelation matrix and SVD of the data matrix are described. The ED/SVD trade-off is discussed.
CitationDuarte, M., Lagunas, M. Eigendecomposition versus singular value decomposition in adaptive array signal processing. "Signal processing", Octubre 1991, vol. 25, núm. 1, p. 25-50. 
URIhttp://hdl.handle.net/2117/97154
DOI10.1016/0165-1684(91)90037-J
ISSN0165-1684
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  • Departament de Teoria del Senyal i Comunicacions - Articles de revista [2.408]
  • A&MP - Grup de Processament d'Arrays i Sistemes Multicanal - Articles de revista [34]
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