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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Identifiability and sloppiness are investigated in this paper for theparameters of a descriptor system based on its frequency response samples. Twometrics are suggested respectively for measuring absolute and relativesloppiness of the parameter vector at a prescribed value. In this descriptorsystem, system matrices are assumed to depend on its parameters through alinear fractional transformation (LFT). When an associated transfer functionmatrix (TFM) is of full normal row rank, a matrix rank based necessary andsufficient condition is derived for parameter identifiability with a set offinitely many frequency responses. This condition can be verified recursivelywhich is computationally quite appealing, especially when the system is of alarge scale. From this condition, an algorithm is suggested to find a set offrequencies with which the frequency responses of the system are capable touniquely determine its parameters. An ellipsoid approximation is given for theset consisting of all the parameter values with which the associated descriptorsystem has a frequency response that deviates within a prescribed distance,from that corresponding to a globally identifiable parameter vector value.Explicit formulas are also derived for the suggested absolute and relativesloppiness metrics.

Frequency Domain Identifiability and Sloppiness of Descriptor Systems with an LFT Structure