• Recovery and enhancement of unknown aperiodic binary signal by adaptive aperiodic stochastic resonance

    • Fulltext

       

        Click here to view fulltext PDF


      Permanent link:
      https://www.ias.ac.in/article/fulltext/pram/095/0036

    • Keywords

       

      Aperiodic stochastic resonance; system with fractional power nonlinearity; aperiodic binary signal; optimisation algorithm.

    • Abstract

       

      In this study, the system with fractional power nonlinearity is introduced into the theory of aperiodic stochastic resonance (ASR). The fractional exponent is a key parameter and its effect on the ASR phenomenon excited by aperiodic binary signal is investigated in this system. Compared to the classical bistable system, the system with fractional power nonlinearity shows better performance. It can adjust not only the noise intensity but also the fractional exponent to enhance weak signal. In the field of signal transmission, pure aperiodic binary signalis usually submerged in the noise and the signal is unknown. Thus, an effective method is proposed based on ASR and moving average. By the method, the unknown aperiodic binary signal can be recovered in the noise background. To improve the efficiency of the signal recovery, the adaptive ASR is realised with the help of adaptive particle swarm optimisation (APSO) algorithm to optimise the parameters. The method may provide some reference to the engineering field.

    • Author Affiliations

       

      CHENGYANG WU1 CHENGJIN WU2

      1. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, People’s Republic of China
      2. School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, People’s Republic of China
    • Dates

       
  • Pramana – Journal of Physics | News

    • Editorial Note on Continuous Article Publication

      Posted on July 25, 2019

      Click here for Editorial Note on CAP Mode

© 2021-2022 Indian Academy of Sciences, Bengaluru.