Mean Exit Time and Escape Probability for Dynamical Systems Driven by Lévy Noises

2014 ◽  
Vol 36 (3) ◽  
pp. A887-A906 ◽  
Author(s):  
T. Gao ◽  
J. Duan ◽  
X. Li ◽  
R. Song
2018 ◽  
Vol 18 (03) ◽  
pp. 1850025
Author(s):  
Xinyong Zhang ◽  
Hui Wang ◽  
Yanjie Zhang ◽  
Haokun Lin

This paper is devoted to studying parameter estimation for a class of stochastic dynamical systems with oscillating coefficients. We show that the homogenized systems faithfully capture the dynamical quantities such as mean exit time and escape probability. Exacting data from observations on the mean exit time (or escape probability) of the original systems, we try to fit the mean exit time (or escape probability) of the homogenized systems by least square method. In this way, we can accurately estimate the unknown parameter in the drift under appropriate assumptions. Furthermore, we conduct some numerical experiments to illustrate our method.


2012 ◽  
Vol 22 (04) ◽  
pp. 1250090 ◽  
Author(s):  
JIAN REN ◽  
CHUJIN LI ◽  
TING GAO ◽  
XINGYE KAN ◽  
JINQIAO DUAN

Effects of non-Gaussian α-stable Lévy noise on the Gompertz tumor growth model are quantified by considering the mean exit time and escape probability of the cancer cell density from inside a safe or benign domain. The mean exit time and escape probability problems are formulated in a differential-integral equation with a fractional Laplacian operator. Numerical simulations are conducted to evaluate how the mean exit time and escape probability vary or bifurcates when α changes. Some bifurcation phenomena are observed and their impacts are discussed.


2012 ◽  
Vol 52 (supplement) ◽  
pp. S84
Author(s):  
Eiji Yamamoto ◽  
Takuma Akimoto ◽  
Yoshinori Hirano ◽  
Masato Yasui ◽  
Kenji Yasuoka

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