Discrete Representation of Signals from Infinite Dimensional Hilbert Spaces with Application to Noise Suppression and Compression

Abstract

Addressed in this thesis is the issue of representing signals from infinite dimensional Hilbert spaces in a discrete form. The discrete representations which are studied come from the irregular samples of a signal dependent transform called the group representation transform, e.g., the wavelet and Gabor transforms. The main issues dealt with are (i) the recoverability of a signal from its discrete representation, (ii) the suppression of noise in a corrupted signal, and (iii) compression through efficient discrete representation.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1993
Accession Number
ADA453215

Entities

People

  • Anthony Teolis

Organizations

  • University of Maryland

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Availability
  • Classification
  • Compression
  • Contracts
  • Hilbert Space
  • Information Operations
  • Instructions
  • Maryland
  • Monitoring
  • Schools
  • Security
  • Standards
  • Universities

Fields of Study

  • Engineering

Readers

  • Acoustics.
  • Approximation Theory.
  • Computer Vision.

Technology Areas

  • Space