Adaptive restoration of unknown samples in certain time-discrete signals

R.N.J. Veldhuis, A.J.E.M. Janssen, L.B. Vries

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

147 Downloads (Pure)


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.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ASSP'85), March 26-29, Tampa, Florida
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Publication statusPublished - 1985


Dive into the research topics of 'Adaptive restoration of unknown samples in certain time-discrete signals'. Together they form a unique fingerprint.

Cite this