Output prediction under scarce data operation: Control applications
The paper deals with the estimation of outputs of a process from scarcely sampled measurements or a missing data sampling pattern, assuming that the process model is known. A wide range of methods to predict estimations of unmeasured outputs in missing-data situations are studied. The main result is the presentation of an algorithm that uses the difference equation of the process, replacing the unknown past values with estimates when necessary.
scientific article; zbMATH DE number 1356087