Detection of non-Gaussian signals: a paradigm for modern statistical signal processing

Lee M. Garth, H. Vincent Poor

Research output: Contribution to journalArticle

36 Scopus citations

Abstract

Non-Gaussian signals arise in a wide variety of applications, including sonar, digital communications, seismology, and radio astronomy. In this tutorial overview, a hierarchical approach to signal modeling and detector design for non-Gaussian signals is described. In addition to being of interest in applications, this problem serves as a paradigm within which most of the areas of active research in statistical signal processing arise. In particular, the methodologies of nonlinear signal processing, higher order statistical analysis, signal representations, and learning algorithms, all can be juxtaposed quite naturally in this framework.

Original languageEnglish (US)
Pages (from-to)1061-1095
Number of pages35
JournalProceedings of the IEEE
Volume82
Issue number7
DOIs
StatePublished - Jul 1 1994
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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