Figure 8. . Linking discrete and continuous state models. This figure uses the same format as previous figures but combines the discrete Bayesian network in Figure 1 with the continuous Bayesian network from Figure 5. Here, the outcomes of the discrete model are now used to select a particular (noisy generalized) hidden cause that determines the (noisy generalized) motion or flow of hidden states generating (noisy generalized) observations. These generalized observations described a trajectory in continuous time.
