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

In this study, the authors focus on estimating the unknown constant latency probability of non‐linear systems with one‐step randomly delayed measurements using maximum likelihood (ML) criterion. A new latency probability estimation algorithm is proposed based on an expectation maximisation approach to obtain 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‐likelihood function is approximately computed based on the currently estimated latency probability, and in the M‐step, the approximate expectation is maximised using the Newton approach. The efficacy of the proposed algorithm is illustrated in a numerical example concerning univariate non‐stationary growth model.