| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5005526 | ISA Transactions | 2006 | 6 Pages |
Abstract
A nonstationary form of the Wiener filter based on a principal components analysis is described for filtering time series data possibly derived from noisy instrumentation. The theory of the filter is developed, implementation details are presented and two examples are given. The filter operates online, approximating the maximum a posteriori optimal Bayes reconstruction of a signal with arbitrarily distributed and non stationary statistics.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Andrew J. Willis,