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Daniel S. Weller

  1. Bayesian Post-Processing Methods for Jitter Mitigation in Sampling.

    Пт, 07/30/2010 - 15:01 — SomNambul
    Authors: Vivek K Goyal, Daniel S. Weller
    Subjects: Applications
    Abstract

    Minimum 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.

  2. On the Estimation of Nonrandom Signal Coefficients from Jittered Samples.

    Чт, 07/29/2010 - 15:01 — SomNambul
    Authors: Vivek K Goyal, Daniel S. Weller
    Subjects: Applications
    Abstract

    This 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.

Math-arch

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