Integrated Adaptive Compression

Abstract

The objective of the Integrated Sensing and Processing (lSP) program was a holistic approach to the design of systems. I) SAIC designed a Joint Source-Channel Coding algorithm, designed to integrate the source data with channel coding. The work resulted it an algorithm that both incorporated a feedback of sensor information into the processing chain and broke through the traditional processing flow of optimizing the compression algorithms based on separate black boxes of source compression and channel coding and modulation. 2) SAIC also designed the Fast Adaptive Modulation algorithm that demonstrated a novel method of nonlinear optimization applied to end-to-end optimization of a radio communications system. Optimization is in least-logs" rather than the more familiar "least-squares" optimization. Least-logs has the advantage that it is less sensitive to outliers than least-squares optimization. As such, it can be applied to curve-fitting and curve-finding applications in noisy images and displays. This methodology measures features, not pixels, with the resulting SNR gain due to integration over the feature.

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 2005
Accession Number
ADA433740

Entities

People

  • Hanna Witzgall
  • J. S. Goldstein
  • Michael D. Zoltowski
  • Robert R. Greene

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Channel Coding
  • Coding
  • Compression
  • Curve Fitting
  • Data Compression
  • Decoding
  • Feedback
  • Intersymbol Interference
  • Modulation
  • Probability
  • Pulse Code Modulation
  • Radio Communications
  • Radio Equipment
  • Signal Processing
  • Spread Spectrum
  • Transmitters

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Distributed Systems and Data Platform Development
  • Radio communications and signal processing.