Name
Abstract | ||
|---|---|---|
Pseudorandom 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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3390/e17041936 | ENTROPY |
Keywords | Field | DocType |
entropy | Entropy power inequality,Mathematical optimization,Maximum entropy thermodynamics,Rényi entropy,Shannon's source coding theorem,Joint entropy,Min entropy,Entropy (information theory),Mathematics,Maximum entropy probability distribution | Journal |
Volume | Issue | Citations |
17 | 4 | 1 |
PageRank | References | Authors |
0.39 | 18 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lingfeng Liu | 1 | 108 | 11.92 |
| Suoxia Miao | 2 | 43 | 5.64 |
| Bocheng Liu | 3 | 4 | 1.09 |