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

The computation required for a switching Kalman Filter (SKF) increasesexponentially with the number of system operation modes. In this paper, acomputationally tractable graph representation is proposed for a switchinglinear dynamic system (SLDS) along with the solution of a minimum-sumoptimization problem for clustering to reduce the switching mode cardinalityoffline, before collecting measurements. It is shown that upon perfect modedetection, the induced error caused by mode clustering can be quantifiedexactly in terms of the dissimilarity measures in the proposed graph structure.Numerical results verify that clustering based on the proposed frameworkeffectively reduces model complexity given uncertain mode detection and thatthe induced error can be well approximated if the underlying assumptions aresatisfied.

Efficient model selection in switching linear dynamic systems by graph clustering