Ambiguity resolution in sparse linear prediction

Hongya Ge, Donald W. Tufts, R. Kumaresan

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

3 Scopus citations

Abstract

We present some results of our analysis of Kumaresan's sparse linear prediction method for estimation of frequencies of sinusoids. Refinements of Kumaresan's method are proposed for the case of two sinusoids which are not close in frequency. When the data is corrupted by additive white Gaussian noise, the probability of correctly resolving ambiguities is used to evaluate the performance. Comparisons between statistical performance analyses and computer simulations demonstrate that the analyses are accurate.

Original languageEnglish (US)
Title of host publicationConference Record of the Asilomar Conference of Signals, Systems & Computers
PublisherPubl by IEEE
Pages1162-1166
Number of pages5
ISBN (Print)0818641207
StatePublished - 1993
Externally publishedYes
EventProceedings of the 27th Asilomar Conference on Signals, Systems & Computers - Pacific Grove, CA, USA
Duration: Nov 1 1993Nov 3 1993

Publication series

NameConference Record of the Asilomar Conference of Signals, Systems & Computers
Volume2
ISSN (Print)1058-6393

Other

OtherProceedings of the 27th Asilomar Conference on Signals, Systems & Computers
CityPacific Grove, CA, USA
Period11/1/9311/3/93

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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