Iterative identification algorithm for tumor model using controlled ARMA model
Publish place: Journal of Mathematical Modeling، Vol: 13، Issue: 1
Publish Year: 1404
Type: Journal paper
Language: English
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Document National Code:
JR_JMMO-13-1_005
Index date: 15 March 2025
Iterative identification algorithm for tumor model using controlled ARMA model abstract
Since system identification of a tumor model is a primary need for controlling tumor model system, accessing suitable and applicable identification methods is a necessary object. In this paper, firstly, for estimating controlled auto-regressive moving average (CARMA) systems, two identification methods, namely generalized projection algorithm (GPA) and two-stage GPA (2S-GPA), are introduced and presented in order to estimate unknown parameters of a specific and vital tumor model. Furthermore, effectiveness of such methods, like convergence rate and estimation error, are discussed and considered. The introduced algorithms are simulated to prove these methods effectiveness, and data derived from the simulations are depicted through tables and figures.
Iterative identification algorithm for tumor model using controlled ARMA model Keywords:
Iterative identification algorithm for tumor model using controlled ARMA model authors
Kiavash Hossein Sadeghi
Department of Electrical Engineering, Faculty of Intelligent Systems Engineering and data science, Persian Gulf University, Bushehr ۷۵۱۶۹, Iran
Abolhassan Razminia
Process Control Laboratory, Faculty of Natural Sciences and Engineering, Abo Akademi University, Turku, Finland
Arash Marashian
Process Control Laboratory, Faculty of Natural Sciences and Engineering, Abo Akademi University, Turku, Finland
