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Large Deviations Principle for Stochastic Delay Differential Equations with Super-linearly Growing Coefficients

  • Diancong Jin,
  • Ziheng Chen,
  • Tau Zhou

摘要

We utilize the weak convergence method to establish the Freidlin–Wentzell large deviations principle (LDP) for stochastic delay differential equations (SDDEs) with super-linearly growing coefficients, which covers a large class of cases with non-globally Lipschitz coefficients. The key ingredient in our proof is the uniform moment estimate of the controlled equation, where we handle the super-linear growth of the coefficients by an iterative argument. Our results allow both the drift and diffusion coefficients of the considered equations to super-linearly grow not only with respect to the delay variable but also to the state variable. This work extends the existing results which develop the LDPs for SDDEs with super-linearly growing coefficients only with respect to the delay variable.