Akademik Veri Yönetim Sistemi
INTERNATIONAL JOURNAL OF COMPUTERS AND COMMUNICATIONS, sa.15, ss.36-43, 2021 (Hakemli Dergi)
In this paper, we study a problem of estimating parameters of sinusoids from noisy data within Bayesian inferential framework. In this context, three different computational schemes such as, Bretthorst’s integral method (BRETTHORST), Gibbs sampling (GIBBS) and parallel tempering (PT) are studied and modifications of their algorithms were tested on data generated from synthetic signals. In addition, our emphasis is given to a comparison of their performances with respect to Cramér-Rao lower bound (CRLB)