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- W2090917504 abstract "We propose a time-varying Wiener filter for nonstationary signal estimation that is robust in a minimax sense. This robust Wiener filter optimizes worst-case performance within novel “p-point” uncertainty classes of nonstationary random processes. Furthermore, it features constant performance within these uncertainty classes and requires less detailed prior knowledge than the ordinary time-varying Wiener filter. We also propose a time–frequency formulation that is intuitively appealing since signal subspaces are replaced by time–frequency regions, and an efficient on-line implementation using local cosine bases. Our theory is illustrated by numerical simulations and a real-data example." @default.
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- W2090917504 date "2000-07-01" @default.
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- W2090917504 title "Minimax robust nonstationary signal estimation based on a p-point uncertainty model" @default.
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