A Non-linear Generalization of Singular Value Decomposition and its Application to Cryptanalysis
Chaotic Dynamics
2009-02-11 v2
Abstract
Singular 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).
Keywords
Cite
@article{arxiv.0711.4910,
title = {A Non-linear Generalization of Singular Value Decomposition and its Application to Cryptanalysis},
author = {Prabhakar G. Vaidya and Sajini Anand P. S and Nithin Nagaraj},
journal= {arXiv preprint arXiv:0711.4910},
year = {2009}
}
Comments
the older version with 14 pages, 3 figures, 1 table, is replaced by the new manuscript with 24 pages, 7 figures and 2 tables