Mean-square random invariant manifolds for stochastic differential equations

We develop a theory of mean-square random invariant manifolds for dynamical systems generated by stochastic differential equations. This is applicable to partial equations driven nonlinear noise. The existence unstable proved the Lyapunov-Perron method based on backward equation involving conditional expectation with respect filtration. stable sets also established but remains open.