Double Decay Parameter Estimation with Autoregressive and Differential Linear Regression

Presented in this paper is a method of formulating a double-decay nuclear process parameter estimation problem as a linear regression problem that can be analytically solved. The resulting linear regression problem is solved for data simulated with electrical circuits and a computer model. In the fi...

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Bibliographic Details
Published in2024 International Conference on Electrical, Computer and Energy Technologies (ICECET pp. 1 - 5
Main Authors Matjelo, Naleli Jubert, Lara, Sekhants'o Paul, Kao, Moruti, Lepekola, Limakatso, Matobako, Mampesi Thato, Singh, Madan
Format Conference Proceeding
LanguageEnglish
Published IEEE 25.07.2024
Subjects
Autoregression
Circuits
Computational modeling
Data models
Double-decay
Integrated circuit modeling
Linear regression
MIMICs
Noise
Noise measurement
Parameter estimation
Robustness
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Summary:Presented in this paper is a method of formulating a double-decay nuclear process parameter estimation problem as a linear regression problem that can be analytically solved. The resulting linear regression problem is solved for data simulated with electrical circuits and a computer model. In the first scenario, with computer-generated data, the linear regression problem leads to an accurate estimation for double-decay process parameters. In the second scenario with circuit-based simulated data, the linear regression solution yields a reasonable solution but it is significantly shifted by the process and measurement noise from the circuit and measuring devices.
DOI:10.1109/ICECET61485.2024.10698202