摘要
在实际应用中,非李普希兹条件是比李普希兹条件更弱的一类条件.本文考虑非李普希兹条件下G-布朗运动驱动的随机微分方程,并建立了此类方程的随机平均原理,证明得出平均后方程的解在均方意义下收敛于原始方程的解.最后,给出一个具体实例来说明本文所建立的随机平均法的有效性.
This paper concerns stochastic differential equations driven by G-Brownian motionunder non-Lipschitz condition which is a much weaker condition with a wider range of applica-tions. Stochastic averaging is established for such non-Lipschitz SDEs where an averaged system is presented to replace the original one in the sense of mean square. An example is presented to illustrate the averaging principle.
出处
《应用概率统计》
CSCD
北大核心
2017年第3期297-309,共13页
Chinese Journal of Applied Probability and Statistics
