Advertisement

Cluster Computing

, Volume 22, Supplement 3, pp 7423–7434 | Cite as

Synchronization between different hyper chaotic systems and dimensions of cellular neural network and its design in audio encryption

  • Guodong LiEmail author
  • Yue Pu
  • Bing Yang
  • Jing Zhao
Article

Abstract

In order to discuss the synchronization characteristic of a class of the cellular neural network and Lorenz hyper chaotic systems. This paper puts forward on the control method between different chaotic and dimensions system, using the controller and base on stability theory of Lyapunov to analysis of the synchronization stability. Finally a synchronization encryption algorithm for audio is presented as a new design. The simulation results show that there is not much correlation between the waveform of the audio document after it’s encrypted with that of the original one. By comparing the spectrum, it further testifies that the encryption effect of this design is remarkable.

Keywords

Cellular neural network Synchronization systems Encryption algorithm Lyapunov stability theory Lorenz hyper chaotic systems 

Notes

Acknowledgements

The paper is supported by National Natural Science Foundation of China (Grant Number: 11461063); The Xinjiang Uygur Autonomous Region Natural Science Foundation (Grant Number: 2017D01A24).

References

  1. 1.
    Kim, K.J., Cho, S.B.: A unified architecture for agent behaviors with selection of evolved neural network modules. Appl. Intell. 25, 253–268 (2006)CrossRefGoogle Scholar
  2. 2.
    Carcenac, M., Redif, S.: A highly scalable modular bottleneck neural network for image dimensionality reduction and image transformation. Appl. Intell. 44, 557–610 (2016)CrossRefGoogle Scholar
  3. 3.
    Han, X.H., Xiong, X.Y., Duan, F.: A new method for image segmentation based on BP neural network and gravitational search algorithm enhanced by cat chaotic mapping. Appl. Intell. 43, 855–873 (2015)CrossRefGoogle Scholar
  4. 4.
    Leon, C.O., Lin, Y.: Cellular neural network: theory. IEEE Trans. Circuits Syst. 35(10), 1257–1272 (1988)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Leon, C.O., Lin, Y.: Cellular neural network: applications. IEEE Trans. Circuits Syst. 35(10), 1273–1290 (1988)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Wang, Y., Guan, Z.H., Wang, G.H.O.: Feedback and adaptive control for the synchronization of chen system via a single variable. Phys. Lett. A 312, 34–40 (2003)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Yassen, M.T.: Feedback and adaptive synchronization of chaotic Lu systems. Chaos Solitons Fractals 23, 1319–1325 (2005)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Li, D., Lu, J.A., Wu, X.Q.: Linearly coupled synchronization of the unified chaotic systems and the Lorenz systems. Chaos Solitons Fractals 23, 79–85 (2005)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Yu, Y., Zhang, S.: The synchronization of linearly bidirectional coupled chaotic systems. Chaos Solitons Fractals 22, 189–197 (2004)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Parameshachari, B.D., Soyjaudah, K.M.S.: Analysis and comparison of fully layered image encryption techniques and partial image encryption techniques. Wirel. Netw. Comput. Intell. 292, 599–604 (2002)Google Scholar
  11. 11.
    Tsai, H.H., Cheng, J.S.: Adaptive signal-dependent audio watermarking based on human auditory system and neural networks. Appl. Intell. 23, 191–206 (2005)CrossRefGoogle Scholar
  12. 12.
    Gonzalo, J., Cicese, B.R., Chen, G., Shieh, L.S.: Fuzzy Chaos synchronization via sampled driving signals. Int. J. Bifurc. Chaos 14, 2721–2733 (2004)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Sun, J., Zhang, Y.: Impulsive control and synchronization of Chua’s oscillators. Math. Comput. Simul. 66, 499–508 (2004)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Liao, T.L., Huang, N.S.: An observer-based approach for chaotic synchronization with applications to secure communications. IEEE Trans. Circuits Syst. I(46), 1144–1150 (1999)CrossRefGoogle Scholar
  15. 15.
    Xiong, W., Xie, W., Cao, J.: Adaptive exponential synchronization of delayed chaotic networks. Physics A 370, 832–842 (2006)CrossRefGoogle Scholar
  16. 16.
    Leon, C.O., Gulak, G.: Cellular neural networks and analog VLSI. Kluwer Academic Publishers (1988)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Applied MathematicsXinjiang University of Finance and EconomicsÜrümqiPeople’s Republic of China
  2. 2.Research center of Xinjiang Social and Economic Statistics of Xinjiang University of Finance and EconomicsXinjiang, ÜrümqiPeople’s Republic of China

Personalised recommendations