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Lyapunov exponent estimates of a class of higher-order stochastic Anderson models
Author(s):
Dan
Tang;
Lijun
Bo
Journal:
Proc. Amer. Math. Soc.
136
(2008),
4033-4043.
MSC (2000):
Primary 60H15, 34A34, 49N60
Posted:
June 5, 2008
MathSciNet review:
2425745
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Abstract:
In this article, we propose a class of high-order stochastic partial differential equations (SPDEs) for spatial dimensions which might be called high-order stochastic Anderson models. This class of the equations is perturbed by a space-time white noise when and by a space-correlated Gaussian noise when . The objectives of this article are to get some estimates on the Lyapunov exponent of the solutions and to study the convergence rates of the chaos expansions of the solutions for the models.
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Additional Information:
Dan
Tang
Affiliation:
School of Mathematical Sciences, Nankai University, Tianjin 300071, People's Republic of China
Email:
dantangcn@yahoo.com.cn
Lijun
Bo
Affiliation:
Department of Mathematics, Xidian University, Xi'an 710071, People's Republic of China
Email:
bolijunnk@yahoo.com.cn
DOI:
10.1090/S0002-9939-08-09442-2
PII:
S 0002-9939(08)09442-2
Keywords:
High-order SPDEs,
stochastic Anderson models,
Lyapunov exponent,
convergence rates.
Received by editor(s):
October 18, 2007
Posted:
June 5, 2008
Additional Notes:
This work was supported by the LPMC at Nankai University and the NSF of China (No. 10471003).
Communicated by:
Edward C. Waymire
Copyright of article:
Copyright
2008,
American Mathematical Society
The copyright for this article reverts to public domain after 28 years from publication.
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