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

Identifiability describes the possibility of determining the values of theunknown parameters that characterize a dynamic system from the knowledge of itsinputs and outputs. This paper finds the general analytical condition thatfully characterizes this property. The condition can be applied to any system,regardless of its complexity and type of nonlinearity. In the presence of timevarying parameters, it is only required that their time dependence beanalytical. In addition, its implementation requires no inventiveness from theuser as it simply needs to follow the steps of a systematic procedure that onlyrequires to perform the calculation of derivatives and matrix ranks. Timevarying parameters are treated as unknown inputs and their identifiability isbased on the very recent analytical solution of the unknown input observabilityproblem. Finally, when a parameter is unidentifiable, the paper also providesan analytical method to determine infinitely many values for this parameterthat are indistinguishable from its true value. The condition is used to studythe identifiability of two nonlinear models in the field of viral dynamics (HIVand Covid-19). In particular, regarding the former, a very popular HIV ODEmodel is investigated, and the condition allows us to automatically find a newfundamental result that highlights a serious error in the current state of theart.

General analytical condition to nonlinear identifiability and its application in viral dynamics