Global minimization of a quadratic functional: neural network approach

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dc.creatorLitinskii, L. B.
dc.creatorMagomedov, B. M.
dc.date2004-12-24
dc.date.accessioned2026-07-07T03:22:18Z
dc.date.available2026-07-07T03:22:18Z
dc.descriptionThe problem of finding out the global minimum of a multiextremal functional is discussed. One frequently faces with such a functional in various applications. We propose a procedure, which depends on the dimensionality of the problem polynomially. In our approach we use the eigenvalues and eigenvectors of the connection matrix.
dc.description4 pages, Lecture on 7th International Conference on Pattern Recognition and Image Analysis PRIA-07-2004, St. Petersburg, Russia
dc.identifierhttps://arxiv.org/abs/cs/0412109
dc.identifierhttp://arxiv.org/abs/cs/0412109
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32542
dc.subjectNeural and Evolutionary Computing
dc.subjectDiscrete Mathematics
dc.titleGlobal minimization of a quadratic functional: neural network approach
dc.typetext

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