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Iterative identification algorithm for tumor model using controlled ARMA model | ||
| Journal of Mathematical Modeling | ||
| مقاله 17، دوره 13، شماره 1، خرداد 2025، صفحه 69-83 اصل مقاله (605.99 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2024.27240.2404 | ||
| نویسندگان | ||
| Kiavash Hossein Sadeghi* 1؛ Abolhassan Razminia2؛ Arash Marashian2 | ||
| 1Department of Electrical Engineering, Faculty of Intelligent Systems Engineering and data science, Persian Gulf University, Bushehr 75169, Iran | ||
| 2Process Control Laboratory, Faculty of Natural Sciences and Engineering, Abo Akademi University, Turku, Finland | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Generalized projection algorithms؛ two-stage identification؛ system identification؛ parameter estimation | ||
| مراجع | ||
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