Filtering and smoothing of boundary and interior measurement data for distributed parameter systems

Four theorems characterizing optimal filtered and smoothed estimates for linear parabolic systems are presented. The models considered include the effects of internal system noise as well as measurement noise. Cases involving measurement data given either on the system's boundary or over its interior are examined. The two theorems on optimal filtering represent extensions and refinements of earlier work; the two theorems on optimal smoothing are new.