PROJECT TITLE :

Latency probability estimation of non-linear systems with one-step randomly delayed measurements

ABSTRACT:

During this study, the authors focus on estimating the unknown constant latency chance of non-linear systems with one-step randomly delayed measurements using maximum likelihood (ML) criterion. A brand new latency probability estimation algorithm is proposed primarily based on an expectation maximisation approach to get an approximate ML estimation of latency probability. The proposed algorithm consists of expectation step (E-step) and the maximisation step (M-step). In the E-step, the expectation of the complete data log-probability operate is approximately computed based on the currently estimated latency likelihood, and within the M-step, the approximate expectation is maximised using the Newton approach. The efficacy of the proposed algorithm is illustrated during a numerical example concerning univariate non-stationary growth model.