  We present a new approach for deriving sampled-data observers from
continuous-time observers that feature an Input-to-Output Stability property
with respect to the output measurement noise and exponential convergence in the
noiseless case. The design approach applies to a wide class of systems and
yields sampled-data observers that inherit all performance characteristics of
the underlying continuous-time observers. The main component of the proposed
sampled-data observer is a novel output predictor that encompasses both
inter-sample predictors and ZOH-predictors.
