Technical Program

Paper Detail

Paper IDS.9.3
Paper Title On the Trackability of Stochastic Processes Based on Causal Information
Authors Baran Tan Bacinoglu, Middle East Technical University, Turkey; Yin Sun, Auburn University, United States; Elif Uysal, Middle East Technical University, United States
Session S.9: Information Measures I
Presentation Lecture
Track Shannon Theory
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract We consider the problem of tracking an unstable stochastic process $X_t$ by using causal knowledge of another stochastic process $Y_t$. 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 R\'{e}nyi entropy, Gallager's reliability function, and the concept of anytime capacity.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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