Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of known samples are discussed. First, this restoration problem is treated as a (nonadaptive) linear minimum variance estimation problem. It is shown that the optimal linear minimum variance interpolator for unknown samples from an autoregressive process uses only a finite neighborhood of known samples, whereas in general this neighborhood is infinite. Second, for signals that can be modeled as autoregressive processes, an adaptive solution to the restoration problem is given.
|Title of host publication||Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ASSP'85), March 26-29, Tampa, Florida|
|Place of Publication||Piscataway|
|Publisher||Institute of Electrical and Electronics Engineers|
|Publication status||Published - 1985|