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


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
Number of pages5
ISBN (Print)0818641207
StatePublished - Dec 1 1993
Externally publishedYes
EventProceedings of the 27th Asilomar Conference on Signals, Systems & Computers - Pacific Grove, CA, USA
Duration: Nov 1 1993Nov 3 1993


OtherProceedings of the 27th Asilomar Conference on Signals, Systems & Computers
CityPacific Grove, CA, USA

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Signal Processing
  • Electrical and Electronic Engineering


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