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/

Zendy Plus

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

Zendy Tools

Zendy Open

We propose an iterative method for joint state and parameter estimation usingmeasurements on a time interval [0,T] for systems that are backward outputstabilizable. Since this time interval is fixed, errors in initial state mayhave a big impact on the parameter estimate. We propose to use the back andforth nudging (BFN) method for estimating the system's initial state and aGauss--Newton step between BFN iterations for estimating the system parameters.Taking advantage of results on the optimality of the BFN method, we show thatfor systems with skew-adjoint generators, the initial state and parameterestimate minimizing an output error cost functional is an attractive fixedpoint for the proposed method. We treat both linear source estimation andbilinear parameter estimation problems.

Iterative observer-based state and parameter estimation for linear systems