TITLE: Universal Minimax Discrete Denoising under Channel Uncertainty
SPEAKER: George Gemelos (Stanford University)
DATE: 2:00 - 3:00 P.M., Tuesday June 22, 2004
LOCATION: Tahoe, 3U (PA)
HOST: Vinay Deolalikar
ABSTRACT:
The goal of a denoising algorithm is to recover a signal from its
noise-corrupted observations. Perfect recovery is seldom possible, and
performance is measured under a given fidelity criterion. For discrete signals
corrupted by a *known* discrete memoryless channel, the DUDE algorithm was
recently shown to perform this task practically and asymptotically optimally,
with no knowledge of statistical properties of the signal.
This talk will address the scenario where, in addition to the lack of
knowledge of the source statistics, there is also uncertainty in the channel
characteristics. We propose a family of denoisers and establish their universal
asymptotic optimality under a minimax criterion we argue appropriate for this
setting. The proposed schemes can be implemented computationally efficiently.
Preliminary experimental results that seem to be indicative of the potential of
these schemes to do well on real data will also be presented.
The talk is based on joint work with Styrmir Sigurjonsson and Tsachy Weissman.
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