Tensor product based modeling of tumor growth

György Eigner, I. Rudas, Aniḱo Szaḱal, L. Kovács

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The application of the Soft Computing based methods, especially, the Tensor Product (TP) transformation has several beneficial properties from the biological modeling and control point of view, because complex, nonlinear processes can be handled by them effectively. Another advantage of these tools consist on the Linear Parameter Varying (LPV) and Linear Matrix Inequality (LMI) based techniques can be easily connected to them. The aim of this study is to develop TP models, which can describe the tumor growth beside anti-Angiogenic treatment. The role of the anti-Angiogenic therapies is to decrease the size of the tumor to operable or maintainable level. From control engineering point of view, the treatment process can be formulated as a control task. In this work, we realized two TP models, which approximates the initial transformed model with high accuracy, regardless the kind of input load and without stability problems. The TP models will be used for TP-based controller design on LMI basis.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages900-905
Number of pages6
Volume2017-January
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - Nov 27 2017
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: Oct 5 2017Oct 8 2017

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period10/5/1710/8/17

Fingerprint

Tumor Growth
Tensor Product
Tensors
Tumors
Product Model
Modeling
Linear matrix inequalities
Matrix Inequality
Linear Inequalities
Soft computing
Soft Computing
Nonlinear Process
Controller Design
Therapy
Tumor
High Accuracy
Engineering
Decrease
Controllers

Keywords

  • Anti-Angiogenic therapy
  • Tensor Product model transformation
  • TP-based modeling
  • Tumor growth model

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

Cite this

Eigner, G., Rudas, I., Szaḱal, A., & Kovács, L. (2017). Tensor product based modeling of tumor growth. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 (Vol. 2017-January, pp. 900-905). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2017.8122724

Tensor product based modeling of tumor growth. / Eigner, György; Rudas, I.; Szaḱal, Aniḱo; Kovács, L.

2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 900-905.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Eigner, G, Rudas, I, Szaḱal, A & Kovács, L 2017, Tensor product based modeling of tumor growth. in 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 900-905, 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, Banff, Canada, 10/5/17. https://doi.org/10.1109/SMC.2017.8122724
Eigner G, Rudas I, Szaḱal A, Kovács L. Tensor product based modeling of tumor growth. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 900-905 https://doi.org/10.1109/SMC.2017.8122724
Eigner, György ; Rudas, I. ; Szaḱal, Aniḱo ; Kovács, L. / Tensor product based modeling of tumor growth. 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 900-905
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