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020 _a9783030576783
_9978-3-030-57678-3
024 7 _a10.1007/978-3-030-57678-3
_2doi
050 4 _aQA267.7
072 7 _aUYA
_2bicssc
072 7 _aCOM014000
_2bisacsh
072 7 _aUYA
_2thema
082 0 4 _a511.352
_223
100 1 _aMitkowski, Paweł J.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_946396
245 1 0 _aMathematical Structures of Ergodicity and Chaos in Population Dynamics
_h[electronic resource] /
_cby Paweł J. Mitkowski.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXII, 97 p. 54 illus., 26 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v312
505 0 _aIntroduction -- Dynamics of the red blood cell system -- Mathematical basics -- Chaos and ergodic theory -- The Lasota-Ważewska Equation -- Lasota equation with unimodal regulation.
520 _aThis book concerns issues related to biomathematics, medicine, or cybernetics as practiced by engineers. Considered population dynamics models are still in the interest of researchers, and even this interest is increasing, especially now in the time of SARS-CoV-2 coronavirus pandemic, when models are intensively studied in order to help predict its behaviour within human population. The structures of population dynamics models and practical methods of finding their solutions are discussed. Finally, the hypothesis of the existence of non-trivial ergodic properties of the model of erythropoietic response dynamics formulated by A. Lasota in the form of delay differential equation with unimodal feedback is analysed. The research can be compared with actual medical data, as well as shows that the structures of population models can reflect the dynamic structures of reality. .
650 0 _aComputational complexity.
_93729
650 0 _aEngineering mathematics.
_93254
650 0 _aComputer science—Mathematics.
_931682
650 0 _aBiomedical engineering.
_93292
650 1 4 _aComputational Complexity.
_93729
650 2 4 _aEngineering Mathematics.
_93254
650 2 4 _aMathematical Applications in Computer Science.
_931683
650 2 4 _aBiomedical Engineering and Bioengineering.
_931842
710 2 _aSpringerLink (Online service)
_946397
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030576776
776 0 8 _iPrinted edition:
_z9783030576790
776 0 8 _iPrinted edition:
_z9783030576806
830 0 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v312
_946398
856 4 0 _uhttps://doi.org/10.1007/978-3-030-57678-3
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c77849
_d77849