This paper considers the problem of adaptive filtering in the presence of uncertainties in the regression data. A recursive procedure is derived that is based on solving local optimization problems that attemps to alleviate the worst-case effect of data uncertainties on filter performance. The resulting procedure turns out to have similarities with leakage-based adaptive filters.
|Number of pages||9|
|Journal||Proceedings of the Allerton Conference on Communication, Control and Computing|
|State||Published - 2000|