Coherence Estimation as Affected by Weighting Functions and Fast Fourier Transform Size.

Abstract

Given two wide-sense stationary random processes, the (complex) coherence function is the (complex) cross power spectral density function divided by the square root of the product of the two (real) auto power spectral density functions. Estimation of the magnitude square of the complex coherence (MSC) with fast Fourier transform (FFT) processing is investigated for synthetic data. The procedure used to partition the given finite time histories into n segments. Each segment, consisting of P data points, is multiplied by a smooth weighting function before computing the FFT. Cross and auto spectra are then averaged over a large number of segments before forming the coherence ratio. It is demonstrated that, when the magnitude of the first derivative of either the auto spectrum or the phase of the complex coherence is large, (1) multiplication by a weighting function is absolutely necessary and (2) P must be large enough to ensure sufficient spectral resolution. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 12, 1972
Accession Number
AD0751576

Entities

People

  • G. Clifford Carter

Organizations

  • Naval Undersea Warfare Center

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Fast Fourier Transforms
  • Mathematics
  • Numbers
  • Spectra
  • Square Roots
  • Stationary
  • Weighting Functions

Readers

  • Approximation Theory.