On the generalized joint linear complexity profile of a class of nonlinear pseudorandom multisequences

Alina Ostafe; Igor E. Shparlinski; Arne Winterhof

doi:10.3934/amc.2010.4.369

On the generalized joint linear complexity profile of a class of nonlinear pseudorandom multisequences

Alina Ostafe^*, Igor E. Shparlinski, Arne Winterhof

^*Corresponding author for this work

School of Computing

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

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Abstract

Recently, multisequences have gained increasing interest for applications in cryptography and quasi-Monte Carlo methods. We study the (generalized) joint linear complexity of a class of nonlinear pseudorandom multisequences introduced by the first two authors as well as the linear complexity of its coordinate sequences. We prove lower bounds which are much stronger than in the case of single sequences since the multidimensional case brings in new and favourable effects.

Original language	English
Pages (from-to)	369-379
Number of pages	11
Journal	Advances in Mathematics of Communications
Volume	4
Issue number	3
DOIs	https://doi.org/10.3934/amc.2010.4.369
Publication status	Published - Aug 2010

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abstract = "Recently, multisequences have gained increasing interest for applications in cryptography and quasi-Monte Carlo methods. We study the (generalized) joint linear complexity of a class of nonlinear pseudorandom multisequences introduced by the first two authors as well as the linear complexity of its coordinate sequences. We prove lower bounds which are much stronger than in the case of single sequences since the multidimensional case brings in new and favourable effects.",

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AB - Recently, multisequences have gained increasing interest for applications in cryptography and quasi-Monte Carlo methods. We study the (generalized) joint linear complexity of a class of nonlinear pseudorandom multisequences introduced by the first two authors as well as the linear complexity of its coordinate sequences. We prove lower bounds which are much stronger than in the case of single sequences since the multidimensional case brings in new and favourable effects.

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On the generalized joint linear complexity profile of a class of nonlinear pseudorandom multisequences

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