Aspects of threshold region mean squared error prediction: Method of interval errors, bounds, Taylor's theorem and extensions

Christ D. Richmond, Larry L. Horowitz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The method of interval errors (MIE) predicts mean-squared error (MSE) performance at low signal-to-noise ratios (SNR) where global errors dominate. It is algorithm specific and enabled by an estimate of asymptotic MSE performance and sidelobe error probabilities. Parameter bounds are adequate representations of the asymptotic MSE in absence of signal model mismatch, but Taylor theorem can account for this mismatch. Herein limitations of bounds versus Taylor's theorem to represent the asymptotic MSE of nonlinear schemes like maximum-likelihood are discussed. Use of first-order Taylor expansions for the purpose of improved approximation of sidelobe error probability is likewise explored.

Original languageEnglish (US)
Title of host publicationConference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Pages13-17
Number of pages5
DOIs
StatePublished - Dec 1 2012
Externally publishedYes
Event46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 - Pacific Grove, CA, United States
Duration: Nov 4 2012Nov 7 2012

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Country/TerritoryUnited States
CityPacific Grove, CA
Period11/4/1211/7/12

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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