Accession Number:

ADA459539

Title:

Adaptive Bayesian Signal Reconstruction with A Priori Model Implementation and Synthetic Examples for X-Ray Crystallography

Descriptive Note:

Journal article

Corporate Author:

PURDUE UNIV LAFAYETTE IN SCHOOL OF ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

1991-02-26

Pagination or Media Count:

38.0

Abstract:

A signal reconstruction problem motivated by X-ray crystallography is approximately solved in a Bayesian statistical approach. The signal is zero-one, periodic, and substantial statistical a priori information is known, which is modeled with a Markov random field. The data are inaccurate magnitudes of the Fourier coefficients of the signal. The solution is explicit and the computational burden is independent of the signal dimension. In this paper, a detailed parameterization of the a priori model appropriate for crystallography is proposed and symmetry-breaking parameters in the solution are used to perform data-dependent adaptation of the estimator. The adaptation attempts to minimize the effects of the spherical model approximation used in the solution. Several examples in one and two dimensions based on simulated data are presented.

Subject Categories:

  • Statistics and Probability
  • Crystallography

Distribution Statement:

APPROVED FOR PUBLIC RELEASE