• Chinese Physics B
  • Vol. 29, Issue 9, (2020)
Jun Zheng1 and Han-Ping Hu1、2、†
Author Affiliations
  • 1School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
  • 2Key Laboratory of Image Information Processing and Intelligent Control, Ministry of Education, Wuhan 430074, China
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    DOI: 10.1088/1674-1056/aba60f Cite this Article
    Jun Zheng, Han-Ping Hu. A novel method of constructing high-dimensional digital chaotic systems on finite-state automata[J]. Chinese Physics B, 2020, 29(9): Copy Citation Text show less
    Chaotic behavior of Chua chaotic system.
    Fig. 1. Chaotic behavior of Chua chaotic system.
    (a) The trajectory of x-dimensional state of the controlled 2DLM. (b) The phase diagram of the controlled 2DLM.
    Fig. 2. (a) The trajectory of x-dimensional state of the controlled 2DLM. (b) The phase diagram of the controlled 2DLM.
    (a) Auto-correlation functions of x-dimensional output of the controlled 2DLM. (b) The frequency distribution of x-dimensional output of the controlled 2DLM.
    Fig. 3. (a) Auto-correlation functions of x-dimensional output of the controlled 2DLM. (b) The frequency distribution of x-dimensional output of the controlled 2DLM.
    Phase diagrams of the controlled 2DLM with different control parameters λ.
    Fig. 4. Phase diagrams of the controlled 2DLM with different control parameters λ.
    Recurrence plots of the controlled 2DLM (x-dimensional state) with different control parameters λ.
    Fig. 5. Recurrence plots of the controlled 2DLM (x-dimensional state) with different control parameters λ.
    Graphs of DET and LAM against different λ of the controlled 2DLM.
    Fig. 6. Graphs of DET and LAM against different λ of the controlled 2DLM.
    Approximate entropy values of the controlled 2DLM (x-dimensional state) with different control parameters λ.
    Fig. 7. Approximate entropy values of the controlled 2DLM (x-dimensional state) with different control parameters λ.
    (a) Bifurcation diagram and (b) Lyapunov exponent of the controlled 2DLM (x-dimensional state).
    Fig. 8. (a) Bifurcation diagram and (b) Lyapunov exponent of the controlled 2DLM (x-dimensional state).
    The phase diagrams. Panels (a), (b), and (c) correspond to original Henon map, uncontrolled and controlled digital Henon maps.
    Fig. 9. The phase diagrams. Panels (a), (b), and (c) correspond to original Henon map, uncontrolled and controlled digital Henon maps.
    Auto-correlation functions. Panels (a), (b), and (c) correspond to original Henon map, uncontrolled and controlled digital Henon maps.
    Fig. 10. Auto-correlation functions. Panels (a), (b), and (c) correspond to original Henon map, uncontrolled and controlled digital Henon maps.
    The frequency distributions. Panels (a), (b), and (c) correspond to original Henon map, uncontrolled and controlled digital Henon maps.
    Fig. 11. The frequency distributions. Panels (a), (b), and (c) correspond to original Henon map, uncontrolled and controlled digital Henon maps.
    The approximate entropies of Henon map, digital Henon map, and controlled Henon map with different finite precisions P.
    Fig. 12. The approximate entropies of Henon map, digital Henon map, and controlled Henon map with different finite precisions P.
    Phase diagrams of the 4DLM: (a) x–y plane, (b) x–z plane, (c) x–v plane, (d) x–y–v space.
    Fig. 13. Phase diagrams of the 4DLM: (a) xy plane, (b) xz plane, (c) xv plane, (d) xyv space.
    (a) Auto-correlation functions of x-dimensional output of the controlled 4DLM. (b) The frequency distribution of x-dimensional output of the controlled 4DLM.
    Fig. 14. (a) Auto-correlation functions of x-dimensional output of the controlled 4DLM. (b) The frequency distribution of x-dimensional output of the controlled 4DLM.
    Approximate entropy values of the controlled 4DLM with different control parameters λ.
    Fig. 15. Approximate entropy values of the controlled 4DLM with different control parameters λ.
    Flowchart of the PRNG.
    Fig. 16. Flowchart of the PRNG.
    Linear complexity of the generated bit sequence.
    Fig. 17. Linear complexity of the generated bit sequence.
    Test indexSuccess proportionMean value of P-values
    Approximate entropy0.9980.5793
    Cumulative sums (forward)0.9880.6546
    Cumulative sums (reverse)0.9880.5311
    FFT0.9960.2088
    Block frequency0.9970.8961
    Frequency0.9890.4159
    Linear complexity0.9990.4407
    Longest runs0.9970.5460
    Overlapping-templates0.9970.8215
    Random excursions0.9920.5184
    Random excursions variant0.9960.5202
    Rank0.9990.6042
    Runs0.9960.4210
    Serial10.9990.2362
    Serial20.9980.1439
    Universal0.9990.5247
    Table 1. Results of NIST SP800-22 tests for test sequences.
    Jun Zheng, Han-Ping Hu. A novel method of constructing high-dimensional digital chaotic systems on finite-state automata[J]. Chinese Physics B, 2020, 29(9):
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