  General nonlinear continuous-time systems are considered for which its state
is estimated via a packet-based communication network. We assume that the
system has multiple sensor nodes, affected by measurement noise, which can
transmit at discrete (non-equidistant) points in time. Moreover, each node can
transmit asynchronously. For this setup, we develop a state estimation
framework, where the transmission instances of the individual sensor nodes can
be generated in either time-triggered or event-triggered fashions. In the
latter case, we guarantee the absence of Zeno behavior by construction. It is
shown that, under the provided design conditions, an input-to-state stability
property is obtained for the estimation error with respect to the measurement
noise and process disturbances and that the state is thus reconstructed
asymptotically in the absence of noise. A numerical case study shows the
strengths of the developed framework.
