Multiresolution Signal and System Analysis and the Analysis and Control of Discrete Event Dynamic Systems.

Abstract

In this report we summarize the following research accomplishments: (a) combining our research on inverse problems with our work on the development of multiresolution stochastic models in order to develop novel and very efficient methods for the fusion and inversion of heterogeneous and multiresolution sensor data; (b) developing a significant extension of the use of our scale recursive multiresolution models for the modeling of spatial phenomena based both on a novel application of the concept of canonical correlations in statistics and on relaxing the relationship between variables in our multiresolution representations and the spatial variables they represent; (c) developing multiresolution models for SAR imagery and the use of these models as thesis for new and very effective likelihood feature for the discrimination of man made objects and natural clutter; and (d) developing a new method for signal approximation and feature extraction known as high resolution pursuit that produces stable and physically meaningful features and the application of this method to high range resolution radar data.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1996
Accession Number
ADA305529

Entities

People

  • Alan S. Willsky

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Data Science
  • Discrimination
  • Extraction
  • Feature Extraction
  • High Resolution
  • Information Science
  • Interdisciplinary Science
  • Inverse Problems
  • Inversion
  • Mathematical Analysis
  • Mathematics
  • Statistical Analysis
  • Statistics

Readers

  • Image Processing and Computer Vision.
  • Theoretical Analysis.

Technology Areas

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