scholarly journals The expected value of the joint linear complexity of periodic multisequences

2003 ◽  
Vol 19 (1) ◽  
pp. 61-72 ◽  
Author(s):  
Wilfried Meidl ◽  
Harald Niederreiter
2008 ◽  
Vol 11 (3) ◽  
pp. 297-304 ◽  
Author(s):  
M. Sethumadhavan ◽  
M. Sindhu ◽  
Chungath Srinivasan ◽  
C. Kavitha

2019 ◽  
Vol 14 (2) ◽  
pp. 33-42
Author(s):  
Zhimin Sun ◽  
Arne Winterhof

AbstractExpansion complexity and maximum order complexity are both finer measures of pseudorandomness than the linear complexity which is the most prominent quality measure for cryptographic sequences. The expected value of the Nth maximum order complexity is of order of magnitude log N whereas it is easy to find families of sequences with Nth expansion complexity exponential in log N. This might lead to the conjecture that the maximum order complexity is a finer measure than the expansion complexity. However, in this paper we provide two examples, the Thue-Morse sequence and the Rudin-Shapiro sequence with very small expansion complexity but very large maximum order complexity. More precisely, we prove explicit formulas for their N th maximum order complexity which are both of the largest possible order of magnitude N. We present the result on the Rudin-Shapiro sequence in a more general form as a formula for the maximum order complexity of certain pattern sequences.


Author(s):  
M. Sindhu ◽  
S. Kumar Sajan ◽  
M. Sethumadhavan

The joint linear complexity and k - error joint linear complexity of an m - fold 2n periodic multisequence can be efficiently computed using Modified Games Chan algorithm and Extended Stamp Martin Algorithm respectively. In this chapter the authors derive an algorithm which, given a constant c and an m – fold 2n periodic binary multisequence S, computes the minimum number k of errors and the associated error multisequence needed over a period of S for bringing the joint linear complexity of S below c . They derived another algorithm for finding the joint linear complexity of 3. 2v periodic binary multisequence.


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