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Evolution of Biological Systems in Random Media: Limit Theorems and Stability

Author: Anatoly Swishchuk; Jianhong Wu
Publisher: Dordrecht : Springer Netherlands, 2003.
Series: Mathematical modelling--theory and applications, 18.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
This is a new book in biomathematics, which includes new models of stochastic non-linear biological systems and new results for these systems. These results are based on the new results for non-linear difference and differential equations in random media. This book contains: -New stochastic non-linear models of biological systems, such as biological systems in random media: epidemic, genetic selection, demography,  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Anatoly Swishchuk; Jianhong Wu
ISBN: 9789401715065 9401715068
OCLC Number: 851377135
Description: 1 online resource (xx, 218 pages).
Contents: 1 Random Media --
2 Limit Theorems for Difference Equations in Random Media --
3 Epidemic Models --
4 Genetic Selection Models --
5 Branching Models --
6 Demographic Models --
7 Logistic Growth Models --
8 Predator-Prey Models.
Series Title: Mathematical modelling--theory and applications, 18.
Responsibility: by Anatoly Swishchuk, Jianhong Wu.

Abstract:

This is a new book in biomathematics, which includes new models of stochastic non-linear biological systems and new results for these systems. These results are based on the new results for non-linear difference and differential equations in random media. This book contains: -New stochastic non-linear models of biological systems, such as biological systems in random media: epidemic, genetic selection, demography, branching, logistic growth and predator-prey models; -New results for scalar and vector difference equations in random media with applications to the stochastic biological systems in 1); -New results for stochastic non-linear biological systems, such as averaging, merging, diffusion approximation, normal deviations and stability; -New approach to the study of stochastic biological systems in random media such as random evolution approach.

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