Source Coding and Adaptive Data Compression for Communication Networks,

Abstract

Coding under a fidelity criteria of a class of sources which emit randomly occurring messages is investigated. This class of sources models information carrying processes entering into communication networks. Messages emitted by computer terminals, teletypes, vocoders, and other such devices serve as actual examples. For this class of sources the rate distortion function is derived, and source coding and converse source coding theorems are proven. Employing these theorems, an operational definition of the rate distortion function in terms of message queueing delay, and transmission delay is presented. This definition relates the rate distortion function with the message network delay which is an important measure of performance of a communication network. Also, for such a class of sources, which emit randomly occurring messages, an adaptive data compression scheme is investigated. This scheme utilizes observations of the network congestion to determine the amount of compression a message receives, with the object of minimizing the message delay for a given distortion level.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1976
Accession Number
ADA035222

Entities

People

  • Howard S. Nussbaum

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Analog Signals
  • Coding
  • Communication Channels
  • Communication Systems
  • Computer Communications
  • Computers
  • Data Compression
  • Information Theory
  • Integral Equations
  • Markov Chains
  • Probability Distributions
  • Random Variables
  • Step Functions
  • Stochastic Processes
  • Theorems
  • Vector Spaces
  • Waveforms

Readers

  • Computer Networking
  • Operations Research
  • Optical Physics and Photonics.