New Algorithm for Detecting Weak Changes in the Mean in a Class of CHARN Models with Application to Welding Electrical Signals
Abstract
In this paper, we propose a new automatic algorithm for detecting weak changes in the mean of a class of piece-wise CHARN models. Through a simulation experiment, we demonstrate its efficacy and precision in detecting weak changes in the mean and accurately estimating their locations. Furthermore, we illustrate the robust performance of our algorithm through its application to welding electrical signals (WES).
Domains
Modeling and SimulationOrigin | Publisher files allowed on an open archive |
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Licence |