On the Trackability of Stochastic Processes Based on Causal Information

Bacinoglu B. T. , Sun Y., UYSAL E.

2020 IEEE International Symposium on Information Theory, ISIT 2020, California, United States Of America, 21 - 26 July 2020, pp.2228-2233 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/isit44484.2020.9174285
  • City: California
  • Country: United States Of America
  • Page Numbers: pp.2228-2233
  • Keywords: tracking conditions, causal information, Holder inequality, Renyi entropy, Gallager's reliability function, Gartner-Ellis limit, anytime capacity, causal estimation, ANYTIME CAPACITY, CHANNELS
  • Middle East Technical University Affiliated: Yes


© 2020 IEEE.We consider the problem of tracking an unstable stochastic process Xt by using causal knowledge of another stochastic process Yt. We obtain necessary conditions and sufficient conditions for maintaining a finite tracking error. We provide necessary conditions as well as sufficient conditions for the success of this estimation, which is defined as order m moment trackability. By-products of this study are connections between statistics such as Rényi entropy, Gallager's reliability function, and the concept of anytime capacity.