Open AccessRECURRENT REPRESENTATION FOR NON-STATIONARY PARAMETER ESTIMATE OF LEAST SQUARES METHOD WITH LEAST DEVIATIONS FROM "ATTRACTION" POINTS FOR BILINEAR DYNAMIC SYSTEMS
Author(s) -
Alexander Slabospitsky
Publication year - 2019
Publication title -
žurnal občislûvalʹnoï ta prikladnoï matematiki
Language(s) - English
Resource type - Journals
eISSN - 2706-9699
pISSN - 2706-9680
DOI - 10.17721/2706-9699.2019.2.04
Subject(s) - mathematics , least squares function approximation , bilinear interpolation , residual sum of squares , representation (politics) , residual , explained sum of squares , moment (physics) , non linear least squares , norm (philosophy) , recursive least squares filter , statistics , algorithm , law , physics , classical mechanics , estimator , politics , political science , adaptive filter
The estimation problem of non-stationary parameter matrices is considered for bilinear discrete dynamic system in the case when for these unknown parameter matrices their ‘attraction’ points are known at any moment. Explicit and recurrent forms of representation are obtained for these parameter estimates of the least squares method with variable forgetting factor and least deviation norm from ‘attraction’ points under non-classical assumptions. The recurrent algorithm is also proposed for corresponding weighted residual sum of squares.