2026-04-17T17:48:22.821Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:395 2013-10-24T21:13:50Z 1

Estimation of nonstationary AR model using the weighted recursive least square algorithm 1995 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/395 http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=480552&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D480552 B. Kovačević M. Veinović M. Milosavljević A new method of estimating time-varying AR models using weighted recursive least square algorithm with a variable forgetting factor is described. The variable forgetting factor is adapted to a nonstationary signal by a generalized likelihood ratio algorithm through the so-called discrimination function which gives a good measure of nonstationarity. In this way we connect the results from the areas of nonstationary signal estimation and jump detection, and obtain an algorithm which exhibits a good tracking performance together with a high parameter estimation accuracy. The feasibility of the approach is demonstrated with both simulation data and real speech signals conferenceObject 1432 1435 10.1109/ICASSP.1995.480552 Proceedings, Vol.2