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Random Evolutionary Systems

- Asymptotic Properties and Large Deviations

Om Random Evolutionary Systems

Within the field of modeling complex objects in natural sciences, which considers systems that consist of a large number of interacting parts, a good tool for analyzing and fitting models is the theory of random evolutionary systems, considering their asymptotic properties and large deviations. In Random Evolutionary Systems we consider these systems in terms of the operators that appear in the schemes of their diffusion and the Poisson approximation. Such an approach allows us to obtain a number of limit theorems and asymptotic expansions of processes that model complex stochastic systems, both those that are autonomous and those dependent on an external random environment. In this case, various possibilities of scaling processes and their time parameters are used to obtain different limit results.

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  • Språk:
  • Engelska
  • ISBN:
  • 9781786307521
  • Format:
  • Inbunden
  • Sidor:
  • 320
  • Utgiven:
  • 19. november 2021
  • Mått:
  • 10x10x10 mm.
  • Vikt:
  • 454 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 27. december 2024
Förlängd ångerrätt till 31. januari 2025

Beskrivning av Random Evolutionary Systems

Within the field of modeling complex objects in natural sciences, which considers systems that consist of a large number of interacting parts, a good tool for analyzing and fitting models is the theory of random evolutionary systems, considering their asymptotic properties and large deviations. In Random Evolutionary Systems we consider these systems in terms of the operators that appear in the schemes of their diffusion and the Poisson approximation. Such an approach allows us to obtain a number of limit theorems and asymptotic expansions of processes that model complex stochastic systems, both those that are autonomous and those dependent on an external random environment. In this case, various possibilities of scaling processes and their time parameters are used to obtain different limit results.

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