Statistical and Numerical Methods in Control and Identification

Abstract

We report on several research projects funded by grant AFOSR-91-0021. Substantial progress has been made in statistical areas, especially in Bayesian analysis and empirical distributions, and in analysis of inverse problems in structures and groundwater modeling. Our numerical studies have focused oil parallel statistical computing in inverse problems, identification in conservation laws, cooling of viscoelastic films, and a general problem involving the estimation of measures. We have computing facilities and the structures lab of Phillips Lab, in order to tailor the statistical and numerical techniques under study to those problems of interest to AFOSR. We have also visited AFESC at Tyndall AFB to discuss mathematical issues in groundwater modeling problems of interest to the Air Force.

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Document Details

Document Type
Technical Report
Publication Date
Dec 31, 1992
Accession Number
ADA264676

Entities

People

  • Ben Fitzpatrick

Organizations

  • University of Tennessee system

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Aircraft Design
  • Algorithms
  • Boltzmann Equation
  • Buildings And Structures
  • Computations
  • Control Systems
  • Equations
  • Estimators
  • Groundwater
  • Identification
  • Integral Equations
  • Inverse Problems
  • Mathematics
  • Probability
  • Statistical Inference

Fields of Study

  • Mathematics

Readers

  • Computational Fluid Dynamics (CFD)
  • Environmental Remediation and Restoration.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms