### Princeton-Rutgers Seminar Series in
Communications and Information Theory

#### Chris Rose and Sergio Verdú, Co-Chairs

Title: Universal Discrete Denoising: Known Channel

Speaker: **Tsachy Weissman**, Stanford University and HP Labs

Date: Thursday November 21, 2002 4:30 pm

Location: Princeton University, Friend 101

**Abstract:**

We propose a discrete denoising algorithm, that, based on the
observation of the output of a known Discrete Memoryless Channel
(DMC), estimates the input sequence to minimize a given fidelity
measure. The algorithm does not assume knowledge of statistical
properties of the input sequence. Yet, it is universal in the sense of
asymptotically performing as well as the optimum denoiser that knows
the input sequence distribution, which is only assumed to be
stationary and ergodic. Moreover, the algorithm is universal also in a
semi-stochastic setting, in which the input is an individual sequence,
and the randomness is due solely to the noise. The proposed denoising
algorithm is practical, as it can be implemented in near-linear time
and with linear storage complexity. Based on joint work with Erik
Ordentlich, Gadiel Seroussi, Sergio Verdu, and Marcelo Weinberger.

Seminar Sponsored by DIMACS Special Focus on Computational Information Theory and Coding.