Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia
This article aims to present a novel neural network observer-based approach in order to estimate the state variables of the nonlinear dynamical system of chronic myelogenous leukemia (CML), specially the number of the infected cells. For this purpose, a two-layer feed forward neural network was appl...
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University of Qom
2022-09-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_1059_fa412bdfc56709bb4fe2f5d0b3fc723b.pdf |
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| _version_ | 1832577581374767104 |
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| author | Yousef Farshidi Reza Ghasemi Aminin Sharafian Ardekani |
| author_facet | Yousef Farshidi Reza Ghasemi Aminin Sharafian Ardekani |
| author_sort | Yousef Farshidi |
| collection | DOAJ |
| description | This article aims to present a novel neural network observer-based approach in order to estimate the state variables of the nonlinear dynamical system of chronic myelogenous leukemia (CML), specially the number of the infected cells. For this purpose, a two-layer feed forward neural network was applied. The weights of both layers are considered variables, depending on time. In order to adjust the neural network weights, the error back propagation learning algorithm was implemented. First of all, in this algorithm, the system outputs are generated according to random weights. Then the error is calculated and propagated back to the network and the weights are updated. This loop is executed until the error asymptotically converges to a small neighbourhood of zero. The better performance of a neural observer would be apparent in comparison with a classical high gain observer. Applying this method for estimating the state variables of cell dynamics results in a reduction in the number of tests and the required samples, which will consequently reduce costs and prevent wasting leukemic patients’ time. |
| format | Article |
| id | doaj-art-6f31e8f26e1046a19f4a7c74fd20049d |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2022-09-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-6f31e8f26e1046a19f4a7c74fd20049d2025-01-30T20:18:08ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752022-09-017212414410.22091/jemsc.2018.1000.10411059Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of LeukaemiaYousef Farshidi0Reza Ghasemi1Aminin Sharafian Ardekani2MSc., Department of Electrical Engineering, faculty of Engineering, University of Qom, Qom, IranAssistant Prof.,Department of Electrical Engineering, faculty of Engineering, University of Qom, Qom, Iran.PhD. Student, Department of Electrical Engineering, faculty of Engineering, University of Qom, Qom, IranThis article aims to present a novel neural network observer-based approach in order to estimate the state variables of the nonlinear dynamical system of chronic myelogenous leukemia (CML), specially the number of the infected cells. For this purpose, a two-layer feed forward neural network was applied. The weights of both layers are considered variables, depending on time. In order to adjust the neural network weights, the error back propagation learning algorithm was implemented. First of all, in this algorithm, the system outputs are generated according to random weights. Then the error is calculated and propagated back to the network and the weights are updated. This loop is executed until the error asymptotically converges to a small neighbourhood of zero. The better performance of a neural observer would be apparent in comparison with a classical high gain observer. Applying this method for estimating the state variables of cell dynamics results in a reduction in the number of tests and the required samples, which will consequently reduce costs and prevent wasting leukemic patients’ time.https://jemsc.qom.ac.ir/article_1059_fa412bdfc56709bb4fe2f5d0b3fc723b.pdfchronic myelogenous leukemiahigh gain observerneural observernonlinear systems |
| spellingShingle | Yousef Farshidi Reza Ghasemi Aminin Sharafian Ardekani Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia مدیریت مهندسی و رایانش نرم chronic myelogenous leukemia high gain observer neural observer nonlinear systems |
| title | Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia |
| title_full | Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia |
| title_fullStr | Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia |
| title_full_unstemmed | Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia |
| title_short | Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia |
| title_sort | designing a neural observer to estimate the state variables of the dynamical system of a specific class of leukaemia |
| topic | chronic myelogenous leukemia high gain observer neural observer nonlinear systems |
| url | https://jemsc.qom.ac.ir/article_1059_fa412bdfc56709bb4fe2f5d0b3fc723b.pdf |
| work_keys_str_mv | AT youseffarshidi designinganeuralobservertoestimatethestatevariablesofthedynamicalsystemofaspecificclassofleukaemia AT rezaghasemi designinganeuralobservertoestimatethestatevariablesofthedynamicalsystemofaspecificclassofleukaemia AT amininsharafianardekani designinganeuralobservertoestimatethestatevariablesofthedynamicalsystemofaspecificclassofleukaemia |