Investigating the Noise Immunity Property of Electro Optic Modulator

  • Aditi DattaEmail author
  • Anjan K. Ghosh
  • Anjan Mukherjee
  • Debashish Bhowmik
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 12)


Chaotic optical signals can be utilized in secure encryption in optical communication systems. Chaos encryption of data is considered to provide higher levels of security than standard cryptographic techniques. Nonlinear system are not free of noise. Nonlinear optical systems like Electro-Optic modulator with an electronic feedback can produce chaotic response. So produced optical signals can be utilized in secure encryption in optical communication systems. Study of nonlinear system remains incomplete without coupling the deterministic system with stochastic process i.e. noise. The influence of noise on nonlinear dynamical system is a very important area of research as noise has a great impact on the evolution of dynamical systems. Here in this paper we have investigated the noise immunity property of Electro Optic modulator and come to know that the map can highly resist to noise. Time response, frequency domain analysis and entropy calculation are the tools those have been used here to check the noisy characteristics of the Electro Optic system.


Noise Chaos Electro Optic modulator FFT Entropy 


  1. 1.
    Strogatz, S.H.: Nonlinear Dynamics and Chaos with Application to Physics, Biology, Chemistry and Engineering, 1st edn. Addison-Wesley Publishing Company, Toronto (1994)Google Scholar
  2. 2.
    Ghosh, A., Verma, P.: Lyapunov exponent of chaos generated by acousto optic modulators with feedback. Opt. Eng. 50, 1–20 (2011)Google Scholar
  3. 3.
    Gastaud, N., Poinsot, S., Larger, L., Merolla, J., Hanna, M., Goedgebuer, J., Malassenet, F.: Electro-optical chaos for multi-10 Gbit/s optical transmissions. Electron. Lett. 40(14), 40–41 (2004)CrossRefGoogle Scholar
  4. 4.
    Lai, D., Chen, G.: Computing the distribution of Lyapunov exponents from time series: the one dimensional case study. Int. J. Bifurcat. Chaos 5, 1721–1726 (1995)CrossRefGoogle Scholar
  5. 5.
    Wolf, A., Swift, J.B., Swinney, H.L., Vastano, J.A.: Determining Lyapunov exponent from a time series. Physica D 16, 285–317 (1985)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Rosenstein, M.T., Collins, J.J., De Luca, C.J.: A practical method for calculating largest Lyapunov exponents from small data sets. Physica D 65, 117–134 (1993)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Ghosh, A.K., Datta, A., Mukherjee, A.: Noise tolerance in optical chaos encrypted communication using nonlinear electro-optic systems. In: Proceedings of Photoics 2018, IIT Delhi (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Aditi Datta
    • 1
    Email author
  • Anjan K. Ghosh
    • 1
  • Anjan Mukherjee
    • 1
  • Debashish Bhowmik
    • 2
  1. 1.Tripura University (A Central University)SuryamaninagarIndia
  2. 2.Tripura Institute of TechnologyNarsingarhIndia

Personalised recommendations