ITR: Universal Discrete Denoising

Princeton University, Princeton NJ

Investigators

Abstract

ABSTRACT 0312839 Verdu, Sergio Princeton U In this proposal we describe an integrated research program on a new research area with a very rich array of applications: the problem of .ltering or denoising of discrete sequences. This statistical signal processing problem arises naturally in a wide range of applications spanning a variety of information technology applications in .elds as varied as computer science, statistics, engineering, astronomy, biology, and information theory. Consider the problem of recovering a signal from a noisy version, which has been corrupted by a known channel. The recovery can assume two major modes depending on the application: noncausal, i.e. it starts once the entire signal is available;and causal, i.e. decisions must be made immediately after each symbol is received. The continuous case, where the input and output alphabets are the real line (or other Euclidean spaces), has received immeasurable attention for over half a century, as witnessed by major contributions to linear .ltering by Wiener, Kolmogorov and Kalman, and to nonlinear .ltering by Donoho and Johnstone.