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http://hdl.handle.net/10397/79118
Title: | A novel algorithm to improve digital chaotic sequence complexity through CCEMD and PE | Authors: | Fan, C Xie, Z Ding, Q |
Issue Date: | 2018 | Source: | Entropy, 2018, v. 20, no. 4, 295 | Abstract: | In this paper, a three-dimensional chaotic system with a hidden attractor is introduced. The complex dynamic behaviors of the system are analyzed with a Poincaré cross section, and the equilibria and initial value sensitivity are analyzed by the method of numerical simulation. Further, we designed a new algorithm based on complementary ensemble empirical mode decomposition (CEEMD) and permutation entropy (PE) that can effectively enhance digital chaotic sequence complexity. In addition, an image encryption experiment was performed with post-processing of the chaotic binary sequences by the new algorithm. The experimental results show good performance of the chaotic binary sequence. | Keywords: | Chaotic system Empirical mode decomposition Image encryption Permutation entropy |
Publisher: | Molecular Diversity Preservation International (MDPI) | Journal: | Entropy | EISSN: | 1099-4300 | DOI: | 10.3390/e20040295 | Rights: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The following publication Fan, C., Xie, Z., & Ding, Q. (2018). A novel algorithm to improve digital chaotic sequence complexity through Ccemd and Pe. Entropy, 20(4), 295 is available at https://doi.org/10.3390/e20040295 |
Appears in Collections: | Journal/Magazine Article |
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Fan_Novel_Algorithm_Improve.pdf | 4.82 MB | Adobe PDF | View/Open |
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