Deconvolution and Estimation of Transfer Function Phase and Coefficients for NonGaussian Linear Processes.

Abstract

NonGaussian linear processes are considered. It is shown that the phase of the transfer function can be estimated under broad conditions. This is not true of Gaussian linear processes and in this sense Gaussian linear processes are a typical. The asymptotic behavior of a phase estimate is determined. The phase estimates make use of bispectral estimates. These ideas are applied to a problem of deconvolution which is effective even when the transfer function is not minimum phase. A number of computational illustrations are given. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 04, 1981
Accession Number
ADA111664

Entities

People

  • K. S. Lii
  • M. Rosenblatt

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Complex Numbers
  • Computational Science
  • Computations
  • Data Science
  • Distribution Functions
  • Frequency
  • Gaussian Processes
  • New York
  • Numbers
  • Polynomials
  • Random Variables
  • Sequences
  • Stationary Processes
  • Stochastic Processes
  • Transfer Functions

Readers

  • Approximation Theory.