| Abstract: |
| Stochastic differential delay equations (SDDEs) are used for describing models that the future states of systems depend on both the present state and their past states. For SDDEs, most of their explicit analytic solutions are unknown and discrete approximations have been studied to obtain numerical solutions of SDDEs. In this talk, we focus on error estimations of the approximate solutions of SDDEs and consider confidence intervals for the approximate solutions. |
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