Absolute Continuity and Mutual Information for Gaussian Mixtures

Abstract

Absolute continuity, process representations, and the Shannon information are considered for problems involving a Gaussian mixture process (N sub t), t in (0,1). N(omega,t)=A(omega)G(omega,t) a.e. dP(omega)dt, where (G sub t) is a Gaussian process and A is a positive random variable independent of (G sub t). Let (Y sub t), t in 0,1, be a second process with nu sub Y and nu sub N the measures induced on R0,1 and mu sub Y and mu sub N the measures induced on L20,1 (Y sub t) has paths a.s. in L20.1. The Cramer-Hida spectral representation and an extension of Girsanov's theorem are used to obtain results on absolute continuity (nu sub Y << nu sub N and mu sub Y << mu sub N) and likelihood ratio in terms of similar results involving a Gaussian mixture local martingale, for which representations are given. These results are then applied to obtain the Shannon mutual information for a communication channel with feedback having (N sub t) as additive noise. Capacity is obtained for the no-feedback channel, subject to an average-energy type of constraint. (jhd)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1988
Accession Number
ADA215185

Entities

People

  • A. F. Gualtierotti
  • C. R. Baker

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Covariance
  • Data Science
  • Differential Equations
  • Eigenvalues
  • Equations
  • Feedback
  • Gaussian Channels
  • Gaussian Processes
  • Hilbert Space
  • Information Science
  • Noise
  • Probability
  • Random Variables
  • Security
  • Statistics
  • Stochastic Processes

Readers

  • Analytical Mechanics
  • Mathematical Modeling and Probability Theory.
  • Statistical inference.