On the Representation of Nonlinear Systems with Gaussian Inputs.

Abstract

An arbitrary nonlinear system with input a Gaussian process, which is such that its output process has finite second moments, admits two kinds of representations; the first in terms of a sequence of deterministic kernels and the second in terms of a single stochastic kernel. We consider here the identification of the sequence of deterministic kernels from the input and output processes, the representation of the system output when its input is a sample function of the Gaussian process, and the relationship of the sequence of kernels mentioned above to the Volterra expansion kernels when the system has a Volterra representation. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1976
Accession Number
ADA032911

Entities

People

  • Stamatis Cambanis
  • Steel T. Huang

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Data Science
  • Gaussian Processes
  • Identification
  • Information Science
  • Integrals
  • Mathematical Analysis
  • Mathematics
  • Nonlinear Systems
  • North Carolina
  • Polynomials
  • Probability
  • Random Variables
  • Sequences
  • Statistical Analysis
  • Statistics

Readers

  • Control Systems Engineering.
  • Statistical inference.