Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13000
Title: Studies on error linear complexity measures for multisequences
Authors: AYINEEDI VENKATESWARLU
Keywords: linear complexity, joint linear complexity, k-error linear complexity, mutlisequences, word-based stream ciphers
Issue Date: 24-Dec-2007
Source: AYINEEDI VENKATESWARLU (2007-12-24). Studies on error linear complexity measures for multisequences. ScholarBank@NUS Repository.
Abstract: In this thesis we develop a theory of $k$-error linearcomplexity for multisequences by introducing three new complexity measures,namely $k$-error joint linear complexity, $k$-error $\mathbb{F}_q$-linearcomplexity and $\vec{\bf k}$-error joint linear complexity. We find analogsof some of the known results in the single sequence case for the multisequencecase. Mainly, we establish various enumeration results and lower bounds on theexpected values of these error linear complexity measures in both the finitelength as well as the periodic case. Multisequences with period length a primeor a prime power receive greater attention in this thesis. In particular,in the latter case, we devise algorithms to compute the error linearcomplexity measures. In this case, we also give formulas for countingfunctions for the $1$-error joint linear complexity.We also present some results on periodic multisequences which possess maximaljoint linear complexity and large error linear complexity, and demonstratethat, for multisequences with suitable parameters, a major proportion ofthem have this property.
URI: http://scholarbank.nus.edu.sg/handle/10635/13000
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
AyineediV.pdf722.71 kBAdobe PDF

OPEN

NoneView/Download

Page view(s)

264
checked on Dec 11, 2017

Download(s)

421
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.