Capacity Bounds and Stochastic Resonance for Binary Input Binary Output Channels

Abstract

In this paper, we discuss the threshold based stochastic resonance behavior of binary input, binary output discrete memoryless channels. We follow the basic model of Chapeau-Blondeau where he showed how the addition of external Gaussian noise could enhance channel capacity, thus providing an optimum channel capacity depending on both the threshold level and noise power of the system. In order to easily approximate channel capacity behavior, we use capacity bounds and approximations.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2012
Accession Number
ADA580143

Entities

People

  • Daniel L. Kang
  • Ira S. Moskowitz
  • Paul Cotae
  • Pedro N. Safier

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Channel Capacity
  • Communication Channels
  • Communication Systems
  • Distribution Functions
  • District Of Columbia
  • Gaussian Distributions
  • Gaussian Noise
  • Information Theory
  • Noise
  • Normal Distribution
  • Numbers
  • Probability
  • Probability Density Functions
  • Random Variables
  • Real Numbers
  • Resonance
  • Simulations

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Radio communications and signal processing.