On Nonlinear Complexity and Shannon’s Entropy of Finite Length Random Sequences
AbstractPseudorandom binary sequences have important uses in many fields, such as spread spectrum communications, statistical sampling and cryptography. There are two kinds of method in evaluating the properties of sequences, one is based on the probability measure, and the other is based on the deterministic complexity measures. However, the relationship between these two methods still remains an interesting open problem. In this paper, we mainly focus on the widely used nonlinear complexity of random sequences, study on its distribution, expectation and variance of memoryless sources. Furthermore, the relationship between nonlinear complexity and Shannon’s entropy is also established here. The results show that the Shannon’s entropy is strictly monotonically decreased with nonlinear complexity. View Full-Text
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Liu, L.; Miao, S.; Liu, B. On Nonlinear Complexity and Shannon’s Entropy of Finite Length Random Sequences. Entropy 2015, 17, 1936-1945.
Liu L, Miao S, Liu B. On Nonlinear Complexity and Shannon’s Entropy of Finite Length Random Sequences. Entropy. 2015; 17(4):1936-1945.Chicago/Turabian Style
Liu, Lingfeng; Miao, Suoxia; Liu, Bocheng. 2015. "On Nonlinear Complexity and Shannon’s Entropy of Finite Length Random Sequences." Entropy 17, no. 4: 1936-1945.