  We consider adaptive maximum-likelihood-type estimators and adaptive
Bayes-type ones for discretely observed ergodic diffusion processes with
observation noise whose variance is constant. The quasi-likelihood functions
for the diffusion and drift parameters are introduced and the polynomial-type
large deviation inequalities for those quasi-likelihoods are shown to see the
convergence of moments for those estimators.
