Peida Tian

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20162021

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3 papers · 1 filter

cs.IT2019

Nonstationary Gauss-Markov Processes: Parameter Estimation and Dispersion

Peida Tian, Victoria Kostina

This paper provides a precise error analysis for the maximum likelihood estimate $a^_{ML} (u_{1}^{n})$ of the parameter $a$ given samples $u_{1}^{n} = (u_{1}, \dots, u_{n})^{'}$ drawn…

cs.IT2018

The Dispersion of the Gauss-Markov Source

Peida Tian, Victoria Kostina

The Gauss-Markov source produces $U_{i} = a U_{i - 1} + Z_{i}$ for $i \geq 1$ , where $U_{0} = 0$ , $∣ a ∣ < 1$ and $Z_{i} \sim N (0, σ^{2})$ are i.i.d. Gaussian random variables. We consider l…

cs.IT2016

Arbitrarily Varying Networks: Capacity-achieving Computationally Efficient Codes

Peida Tian, Sidharth Jaggi, Mayank Bakshi +1

We consider the problem of communication over a network containing a hidden and malicious adversary that can control a subset of network resources, and aims to disrupt communicatio…