On robust detection of discrete-time stochastic signals

H. V. Poor, M. Mami, J. B. Thomas

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

The problem of designing robust systems for the detection of stochastic signals in noise is considered for the large-sample-size, small-signal case. By applying two previously-established models for the detection of stochastic signals, known results for the robust detection of deterministic signals are extended on a limited basis to the stochastic- signal case. The proposed detectors are seen to be robust over a class of possible noise statistics, based on a Huber-Tukey mixture model, which contains noises characterized by heavy-tailed probability density functions. In addition, numerical results are presented which verify the robustness property of the proposed detectors over wider classes of noise mixtures.

Original languageEnglish (US)
Pages (from-to)29-53
Number of pages25
JournalJournal of the Franklin Institute
Volume309
Issue number1
DOIs
StatePublished - Jan 1980
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Applied Mathematics

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