This repository contains code to reproduce the results presented in "Likelihood-Based Adaptive Learning in Stochastic State-Based Models" by Peter Vieting, Rodrigo C. de Lamare, Lukas Martin, Guido Dartmann and Anke Schmeink and published in the IEEE Signal Processing Letters.
The repository contains Matlab code of the proposed algorithms. The folder General contains the files with the algorithms' implementations and additional functions used by them. In the folder final, there are scripts which produce the results presented in the paper. In these scripts, it is possible to see how to use the algorithms. The main file to reproduce Fig. 4 is SPN_Comparison.m while SPN_EMSE.m is the main file to reproduce Fig. 5.
Please note that the LB-DAAGD approach from the paper is called VSS-DAAGD in the code.