Bayesian Estimation for Continous-Time Sparse Stochastic Processes
Arash Amini, BIG and Sharif Univ. of Technology, Tehran, Iran

Seminar • 11 October 2010

Abstract
In this talk, Arash will present a continuous-time stochastic model for the signals which have sparse representation in a transformation domain ; e.g., piecewise constant signals. Based on the characteristic forms, some joint probability distributions are derived which are useful for estimation problems such as denoising and interpolation. He will explain the case of piecewise constant signals in more detail and compare the MAP estimator with TV minimizer. He will also briefly point out some results regarding compressibility of probability distributions.