Nonsearch paradigm for large-scale parameter-identification problems in dynamical systems related to oncogenic hyperplasia

E. Mamontov, Andrei Koptioug

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции


In many engineering and biomedical problems there is a need to identify parameters of the systems from experimental data. A typical example is the biochemical-kinetics systems describing oncogenic hyperplasia where the dynamical model is nonlinear and the number of the parameters to be identified can reach a few hundreds. Solving these large-scale identification problems by the local- or global-search methods can not be practical because of the complexity and prohibitive computing time. These difficulties can be overcome by application of the non-search techniques which are much less computation- demanding. The present work proposes key components of the corresponding mathematical formulation of the nonsearch paradigm. This new framework for the nonlinear large-scale parameter identification specifies and further develops the ideas of the well-known approach of A. Krasovskii. The issues are illustrated with a concise analytical example. The new results and a few directions for future research are summarized in a dedicated section.

Язык оригиналаАнглийский
Название основной публикацииSystems Control, Modeling and Optimization
Подзаголовок основной публикацииProceedings of the 22nd IFIP TC7 Conference held from July 18-22, 2005, in Turin, Italy
РедакторыF. Ceragioli, L. Pandolfi, A. Dontchev, H. Furuta, K. Marti
Число страниц10
СостояниеОпубликовано - 2006
Опубликовано для внешнего пользованияДа

Серия публикаций

НазваниеIFIP International Federation for Information Processing
ISSN (печатное издание)1571-5736

ASJC Scopus subject areas

  • Information Systems and Management

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