A Non-linear Generalization of Singular Value Decomposition and its Application to Cryptanalysis

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dc.creatorVaidya, Prabhakar G.
dc.creatorS, Sajini Anand P.
dc.creatorNagaraj, Nithin
dc.date2007-11-30
dc.date2009-02-11
dc.date.accessioned2026-07-07T12:39:39Z
dc.date.available2026-07-07T12:39:39Z
dc.descriptionSingular Value Decomposition (SVD) is a powerful tool in linear algebra.We propose an extension of SVD for both the qualitative detection and quantitative determination of nonlinearity in a time series. The paper illustrates nonlinear SVD with the help of data generated from nonlinear maps and flows (differential equations).
dc.descriptionthe older version with 14 pages, 3 figures, 1 table, is replaced by the new manuscript with 24 pages, 7 figures and 2 tables
dc.identifierhttps://arxiv.org/abs/0711.4910
dc.identifierhttp://arxiv.org/abs/0711.4910
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/219184
dc.subjectChaotic Dynamics
dc.titleA Non-linear Generalization of Singular Value Decomposition and its Application to Cryptanalysis
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