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A subgradient algorithm for data-rate optimization in the remote state estimation problem

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posted on 2023-06-10, 00:51 authored by Christoph Kawan, Sigurdur Hafstein, Peter GieslPeter Giesl
In the remote state estimation problem, an observer tries to reconstruct the state of a dynamical system at a remote location, where no direct sensor measurements are available. The observer only has access to information sent through a digital communication channel with a finite capacity. The recently introduced notion of restoration entropy provides a way to determine the smallest channel capacity above which an observer can be designed that observes the system without a degradation of the initial observation quality. In this paper, we propose a subgradient algorithm to estimate the restoration entropy via the computation of an appropriate Riemannian metric on the state space, which allows us to determine the approximate value of the entropy from the time-one map (in the discrete-time case) or the generating vector field (for ODE systems), respectively.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

SIAM Journal on Applied Dynamical Systems

ISSN

1536-0040

Publisher

Society of Industrial and Applied Mathematics

Issue

4

Volume

20

Page range

2142-2173

Department affiliated with

  • Mathematics Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2021-09-06

First Open Access (FOA) Date

2021-09-16

First Compliant Deposit (FCD) Date

2021-09-03

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