Nonsearch Paradigm for Large-Scale Parameter-Identification Problems in Dynamical Systems Related to Oncogenic Hyperplasia

  • E. Mamontov
  • A. Koptioug
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 202)


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.


nonlinear dynamic system non-search parameter identification Krasovskii method biochemical kinetics 


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© International Federation for Information Processing 2006

Authors and Affiliations

  • E. Mamontov
    • 1
  • A. Koptioug
    • 2
  1. 1.Department of PhysicsGothenburg UniversityGothenburgSweden
  2. 2.Department of Electronics, Institute of Information Technology and MediaMid Sweden UniversityÖstersundSweden

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