English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We investigate state estimation of linear systems over channels having afinite state not known by the transmitter or receiver. We show that similar tomemoryless channels, zero-error capacity is the right figure of merit forachieving bounded estimation errors. We then consider finite-state, worst-caseversions of the common erasure and additive noise channels models, in which thenoise is governed by a finite-state machine without any statistical structure.Upper and lower bounds on their zero-error capacities are derived, revealing aconnection with the {\em topological entropy} of the channel dynamics. Separatenecessary and sufficient conditions for bounded linear state estimation errorsvia such channels are obtained. These estimation conditions bring together thetopological entropies of the linear system and the discrete channel.

Bounded State Estimation over Finite-State Channels: Relating Topological Entropy and Zero-Error Capacity