Daniel S. Weller
Bayesian Post-Processing Methods for Jitter Mitigation in Sampling.
Fri, 07/30/2010 - 15:01 — SomNambulAuthors: Vivek K Goyal, Daniel S. Weller
Subjects: Applications
AbstractMinimum mean squared error (MMSE) estimators of signals from samples
corrupted by jitter (timing noise) and additive noise are nonlinear, even when
the signal prior and additive noise have normal distributions. This paper
develops stochastic algorithms based on Gibbs sampling and slice sampling to
approximate optimal MMSE estimators in this Bayesian formulation. Simulations
demonstrate that these nonlinear algorithms can improve significantly upon the
linear MMSE estimator.On the Estimation of Nonrandom Signal Coefficients from Jittered Samples.
Thu, 07/29/2010 - 15:01 — SomNambulAuthors: Vivek K Goyal, Daniel S. Weller
Subjects: Applications
AbstractThis paper examines the problem of estimating the parameters of a bandlimited
signal from samples corrupted by random jitter (timing noise) and additive iid
Gaussian noise, where the signal lies in the span of a finite basis. For the
presented classical estimation problem, the Cramer-Rao lower bound (CRB) is
computed, and an Expectation-Maximization (EM) algorithm approximating the
maximum likelihood (ML) estimator is developed. Simulations are performed to
study the convergence properties of the EM algorithm and compare the
performance both against the CRB and a basic linear estimator.
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