Discrimination between Stationary Gaussian Processes, Large Sample Results

Abstract

The structure of the asymptotic log-likelihood ratio decision procedure for the discrimination of alternative stationary zero mean multivariate Gaussian processes is developed. The log-likelihood ratio statistic is shown to be asymptotically normally distributed. New time and frequency domain formulas for the conditional mean (The Kullback-Liebler information measure) and variance of the log-likelihood ratio statistic under the alternative hypotheses are given and the probability of misclassification is shown to be bounded exponentially with n, the number of observations.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1977
Accession Number
ADA044893

Entities

People

  • Will Gersch

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computations
  • Data Science
  • Discrimination
  • Distribution Functions
  • Frequency
  • Frequency Domain
  • Gaussian Processes
  • Information Science
  • Mathematical Filters
  • Normal Distribution
  • Observation
  • Probability
  • Random Variables
  • Stationary
  • Statistical Algorithms
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Regression Analysis.