Representation and Estimation of Cyclostationary Processes

Abstract

Random signal processes which have been subjected to some form of repetitive operation such a sampling, scanning or multiplexing will usually exhibit statistical properties which vary periodically with time. Systems analysts have tended, for the most part, to treat these cyclostationary processes as though they were stationary. This is done simply by averaging the statistical parameters (mean, variance, etc.) over one cycle. The first chapter of the report features a detailed historical account of the development and application of cyclostationary processes. The second chapter is an extensive treatment of the topics of transformation, generation, and modelling of cyclostationary processes. The third chapter contains an in-depth treatment of series representations for cyclostationary processes, and their autocorrelation functions, and other periodic kernels. The fourth chapter addresses itself to the problem of least-mean-squared-error linear estimation (optimum filtering) of cyclostationary processes.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1972
Accession Number
AD0753125

Entities

People

  • William A. Gardner

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Amplitude Modulation
  • Communication Channels
  • Communication Systems
  • Communications Techniques
  • Doppler Effect
  • Ergodic Processes
  • Filters
  • Filtration
  • Frequency Shift
  • Integral Equations
  • Mathematical Filters
  • Modulation
  • Modulators
  • Multiplexing
  • Periodic Variations
  • Random Variables
  • Time Division Multiplexing

Readers

  • Computer Science.
  • Radio communications and signal processing.
  • Statistical inference.