Method of statistical imitation, its creator S. Ulam and basic principles of application for random processes modeling

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dc.citation.epage30
dc.citation.issue1
dc.citation.journalTitleКомп'ютерні системи проектування. Теорія і практика
dc.citation.spage21
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationLviv Polytechynic National University
dc.contributor.authorКособуцький, П.
dc.contributor.authorЛобур, М.
dc.contributor.authorМатвіїв-Лозинська, Ю.
dc.contributor.authorKosobutskyy, P.
dc.contributor.authorLobur, M.
dc.contributor.authorMatviiv-Lozynska, Yu.
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-03-08T09:39:56Z
dc.date.available2023-03-08T09:39:56Z
dc.date.created2021-08010
dc.date.issued2021-08010
dc.description.abstractВисвітлено досягнення відомих львів’ян – автора методу Монте-Карло С. Улама та математика Марка Каца. Коротко розкрито методичні алгоритми Монте-Карло моделювання статистичних закономірностей проходження світла крізь оптично неоднорідні середовища.
dc.description.abstractThe article is dedicated to famous Lviv residents, the author of the Monte Carlo method, and mathematician Mark Kac. The method of Monte Carlo methodical algorithms for modeling statistical regularities of light passage through optically inhomogeneous media is briefly described in the article.
dc.format.extent21-30
dc.format.pages10
dc.identifier.citationKosobutskyy P. Method of statistical imitation, its creator S. Ulam and basic principles of application for random processes modeling / P. Kosobutskyy, M. Lobur, Yu. Matviiv-Lozynska // Computer Design Systems. Theory and Practice. — Lviv : Lviv Politechnic Publishing House, 2021. — Vol 3. — No 1. — P. 21–30.
dc.identifier.citationenKosobutskyy P., Lobur M., Matviiv-Lozynska Yu. (2021) Method of statistical imitation, its creator S. Ulam and basic principles of application for random processes modeling. Computer Design Systems. Theory and Practice (Lviv), vol. 3, no 1, pp. 21-30.
dc.identifier.doihttps://doi.org/10.23939/cds2021.01.021
dc.identifier.issn2707-6784
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/57566
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofКомп'ютерні системи проектування. Теорія і практика, 1 (3), 2021
dc.relation.ispartofComputer Design Systems. Theory and Practice, 1 (3), 2021
dc.relation.references1. Kosobutskyy, P. Statistical and Monte-Carlo Algoritms for Simulation of Random Processes in macro- and microsystems using MathCAD. Lviv: LPNU, 2014.
dc.relation.references2. Wang, L., Jacques, S. Monte-Carlo modeling of light transport in Multi-layer Tissues in Standart C. University of Texas. Anderson Cancer Center, 1992.
dc.relation.references3. Wang, L., Jacques, S., Zheng, L. MCML-Monte-Carlo modeling of light transport in multi-layer tissues. Computer Methods and Programs in Biomedicine, 1995, Vol. 47, 131–146. https://doi.org/10.1016/0169-2607(95)01640-F.
dc.relation.references4. Binzoni, T., Leung, T. S. Gandjbakhche et.al. The use of the Heyey – Greenstein phase function in Monte Carlo simuliations in biomedical optics. Phys. Med. Biol., 2006, Vol. 51, N313–N322. https://doi.org/10.1088/0031-9155/51/17/N04.
dc.relation.references5. Prahl, S. A. Light transport in tissue, PhD dissertation, University of Texas at Austin, 1988.
dc.relation.references6. Wang, L. H., Jacques, S. L. Monte Carlo Modeling of Light Transport in Multi-layered Tissues in Standard C, University of Texas, M. D. Anderson Cancer Center, 1992.
dc.relation.references7. Wang, L. H., Jacques, S. L., Zheng, L.-Q MCML-Monte Carlo modeling of photon transport in multi-layered tissues, Computer Methods and Programs in Biomedicine, 1995, Vol. 47, 131–146. https://doi.org/10.1016/0169-2607(95)01640-F.
dc.relation.references8. Zhu, C., Liu, Q. Review of Monte Carlo modeling of light transport in tissues. Journal of Biomedical Optics 18(5), 050902, May 2013. https://doi.org/10.1117/1.JBO.18.5.050902.
dc.relation.references9. Jacques, S. L., Optical properties of biological tissues: a review, Phys. Med. Biol., 2013, 58, 37–61. Vo-Dinh T., Biomedical Photonics handbook, CRC Press, March 2003.
dc.relation.references10. Wang, L. V., Wu, H. І. Biomedical Optics: Principles and Imaging, Wiley, 2007.
dc.relation.references11. Boas, D. A., Pitris, C., Ramanujam, N., Handbook of Biomedical Optics. CRC Press June 2011.
dc.relation.references12. Kosobutskyy, P. Envelope Method in Fabry-Perot Interferometry. Lviv: LPNU, 2013.
dc.relation.references13. PH36010 Numerical Methods. Writing Programs in MathCAD.
dc.relation.references14. Salerud, E. G. Biomedical Optics: Light scattering in Tissue by Monte Carlo Simulation, IMT October 2006.
dc.relation.referencesen1. Kosobutskyy, P. Statistical and Monte-Carlo Algoritms for Simulation of Random Processes in macro- and microsystems using MathCAD. Lviv: LPNU, 2014.
dc.relation.referencesen2. Wang, L., Jacques, S. Monte-Carlo modeling of light transport in Multi-layer Tissues in Standart C. University of Texas. Anderson Cancer Center, 1992.
dc.relation.referencesen3. Wang, L., Jacques, S., Zheng, L. MCML-Monte-Carlo modeling of light transport in multi-layer tissues. Computer Methods and Programs in Biomedicine, 1995, Vol. 47, 131–146. https://doi.org/10.1016/0169-2607(95)01640-F.
dc.relation.referencesen4. Binzoni, T., Leung, T. S. Gandjbakhche et.al. The use of the Heyey – Greenstein phase function in Monte Carlo simuliations in biomedical optics. Phys. Med. Biol., 2006, Vol. 51, N313–N322. https://doi.org/10.1088/0031-9155/51/17/N04.
dc.relation.referencesen5. Prahl, S. A. Light transport in tissue, PhD dissertation, University of Texas at Austin, 1988.
dc.relation.referencesen6. Wang, L. H., Jacques, S. L. Monte Carlo Modeling of Light Transport in Multi-layered Tissues in Standard C, University of Texas, M. D. Anderson Cancer Center, 1992.
dc.relation.referencesen7. Wang, L. H., Jacques, S. L., Zheng, L.-Q MCML-Monte Carlo modeling of photon transport in multi-layered tissues, Computer Methods and Programs in Biomedicine, 1995, Vol. 47, 131–146. https://doi.org/10.1016/0169-2607(95)01640-F.
dc.relation.referencesen8. Zhu, C., Liu, Q. Review of Monte Carlo modeling of light transport in tissues. Journal of Biomedical Optics 18(5), 050902, May 2013. https://doi.org/10.1117/1.JBO.18.5.050902.
dc.relation.referencesen9. Jacques, S. L., Optical properties of biological tissues: a review, Phys. Med. Biol., 2013, 58, 37–61. Vo-Dinh T., Biomedical Photonics handbook, CRC Press, March 2003.
dc.relation.referencesen10. Wang, L. V., Wu, H. I. Biomedical Optics: Principles and Imaging, Wiley, 2007.
dc.relation.referencesen11. Boas, D. A., Pitris, C., Ramanujam, N., Handbook of Biomedical Optics. CRC Press June 2011.
dc.relation.referencesen12. Kosobutskyy, P. Envelope Method in Fabry-Perot Interferometry. Lviv: LPNU, 2013.
dc.relation.referencesen13. PH36010 Numerical Methods. Writing Programs in MathCAD.
dc.relation.referencesen14. Salerud, E. G. Biomedical Optics: Light scattering in Tissue by Monte Carlo Simulation, IMT October 2006.
dc.relation.urihttps://doi.org/10.1016/0169-2607(95)01640-F
dc.relation.urihttps://doi.org/10.1088/0031-9155/51/17/N04
dc.relation.urihttps://doi.org/10.1117/1.JBO.18.5.050902
dc.rights.holder© Національний університет „Львівська політехніка“, 2021
dc.rights.holder© Kosobutskyy P., Lоbur M., Matviiv-Lozynska Yu., 2021
dc.subjectметод Монте-Карло
dc.subjectрозсіяння світла мутними середовищами
dc.subjectMonte Carlo method
dc.subjectlight scattering by turbid media
dc.subject.udc53 (075.8)
dc.subject.udc519.21
dc.subject.udc621.417
dc.titleMethod of statistical imitation, its creator S. Ulam and basic principles of application for random processes modeling
dc.title.alternativeМетод статистичної імітації С.Улама та основні принципи застосування для моделювання випадкових процесів
dc.typeArticle

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Комп'ютерні системи проектування теорія і практика. – 2021. – Том 3, № 1