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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We link optimal filtering for hidden Markov models to the notion of dualityfor Markov processes. We show that when the signal is dual to a process thathas two components, one deterministic and one a pure death process, and withrespect to functions that define changes of measure conjugate to the emissiondensity, the filtering distributions evolve in the family of finite mixtures ofsuch measures and the filter can be computed at a cost that is polynomial inthe number of observations. Special cases of our framework include the Kalmanfilter, and computable filters for the Cox-Ingersoll-Ross process and theone-dimensional Wright-Fisher process, which have been investigated before. Thedual we obtain for the Cox-Ingersoll-Ross process appears to be new in theliterature.

Optimal filtering and the dual process