On generalized signal-to-noise ratios in quadratic detection

Richard J. Barton, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


The generalized signal-to-noise ratio (GSNR) is a measure of performance often used in evaluating binary hypothesis testing procedures. In this paper, we investigate the properties of the GSNR as applied to the evaluation of quadratic detectors with Gaussian hypotheses. Appealing to reproducing kernel Hilbert space theory, we give a representation for the GSNR that is particularly useful for evaluating extremal properties. Finally, we discuss an alternative performance measure that is both intuitively appealing and superior to the GSNR in some respects.

Original languageEnglish (US)
Pages (from-to)81-91
Number of pages11
JournalMathematics of Control, Signals, and Systems
Issue number1
StatePublished - Mar 1992

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Control and Optimization
  • Applied Mathematics


  • Deflection ratio
  • Generalized signal-to-noise ratio
  • Quadratic detection
  • Reproducing kernel Hilbert space
  • Stochastic signal detection


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