5 citations · 7 across the 6 of their papers we have counts for
7 papers
Reducing the LQG Cost with Minimal Communication
Oron Sabag, Peida Tian, Victoria Kostina +1
We study the linear quadratic Gaussian (LQG) control problem, in which the controller's observation of the system state is such that a desired cost is unattainable. To achieve the…
Reinforcement Learning Evaluation and Solution for the Feedback Capacity of the Ising Channel with Large Alphabet
Ziv Aharoni, Oron Sabag, Haim Henri Permuter
We propose a new method to compute the feedback capacity of unifilar finite state channels (FSCs) with memory using reinforcement learning (RL). The feedback capacity was previousl…
Computing the Feedback Capacity of Finite State Channels using Reinforcement Learning
Ziv Aharoni, Oron Sabag, Haim Henry Permuter
In this paper, we propose a novel method to compute the feedback capacity of channels with memory using reinforcement learning (RL). In RL, one seeks to maximize cumulative rewards…
Graph-Based Encoders and their Performance for Finite-State Channels with Feedback
Oron Sabag, Bashar Huleihel, Haim Permuter
The capacity of unifilar finite-state channels in the presence of feedback is investigated. We derive a new evaluation method to extract graph-based encoders with their achievable…
Feedback Capacity and Coding for the -RLL Input-Constrained BEC
Ori Peled, Oron Sabag, Haim H. Permuter
The input-constrained binary erasure channel (BEC) with strictly causal feedback is studied. The channel input sequence must satisfy the -runlength limited (RLL) constraint,…
A Single-Letter Upper Bound on the Feedback Capacity of Unifilar Finite-State Channels
Oron Sabag, Haim H. Permuter, Henry D. Pfister
An upper bound on the feedback capacity of unifilar finite-state channels (FSCs) is derived. A new technique, called the -contexts, is based on a construction of a directed grap…