Advances in Control and Signal Processing

Abstract

The research reported herein, has led to significant advances in high resolution spectral analysis of time series impacting upon sensor technology and upon application areas such as radar and medical imaging. The research is based on the initial discovery that (weighted) covariance statistics i.e., statistics which are more general than the traditional autocorrelation function, allow for a superior resolution of the power spectrum of a time-series. The work comprises of the development of computational theory and the development of a spectrum of analytical tools for (i) parametrizing all power spectra which are consistent with given data5 (ii) incorporating prior information in spectral estimation, and (iii) fusion of covariance statistics obtained by different sensors Research on a parallel effort in control design methodologies has led to advances in robustness analysis and optimal control of oscillatory systems

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2003
Accession Number
ADA415547

Entities

People

  • Tryphon T. Georgiou

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Autocorrelation
  • Computer Science
  • Computer Vision
  • Covariance
  • Data Science
  • High Resolution
  • Information Processing
  • Information Science
  • Mathematics
  • Power Spectra
  • Signal Processing
  • Spectra
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • Synthetic Aperture Radar

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Image Processing and Computer Vision.