Parameter Estimation for Bursty-Intermittent Observations Patlamali-Kesikli Gozlemler icin Parametre Kestirimi


Cagatay Candan Ç.

28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Turkey, 5 - 07 October 2020 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu49456.2020.9302359
  • City: Gaziantep
  • Country: Turkey
  • Keywords: Cramer-Rao bound., Expectation-maximization method, Hidden Markov models, Parameter estimation

Abstract

© 2020 IEEE.Parameter estimation problem is examined in the setting where the noise power is allowed to change from sample to sample. Parameters of the noise source is assumed to be generated by a Markov chain whose state sequence is not known by the observation system. Expectation-maximization algorithm is applied for the estimation of desired parameter with the inclusion of unknown state vector of the Markov chain realization as a latent variable. The suggested scheme can be utilized in applications with bursty noise and/or intermittent signals.