Bayesian parameter estimation using periodic cost functions

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


In this paper, a new method for Bayesian periodic parameter estimation is derived using periodic cost functions. The method, named parameter estimation via root finding (PERF), is based on Fourier series representation of the Bayes periodic-risk functions. The PERF method is implemented for minimum cyclic error, minimum absolute periodic error, and minimum mean-square-periodic-error (MSPE) estimators and the corresponding estimators are derived. The periodic estimators are applied to direction-of-arrival and phase estimation problems and compared with the minimum mean-square-error and maximum a posteriori probability estimators, and the periodic Ziv-Zakai lower bound in terms of MSPE.

Original languageEnglish
Article number6062425
Pages (from-to)1229-1240
Number of pages12
JournalIEEE Transactions on Signal Processing
Issue number3
StatePublished - 1 Mar 2012


  • Bayesian parameter estimation
  • direction of arrival estimation
  • mean-square-periodic-error (MSPE)
  • minimum mean-square-error (MMSE)
  • parameter estimation via root finding
  • periodic Ziv-Zakai lower bound
  • periodic estimation
  • phase estimation

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Bayesian parameter estimation using periodic cost functions'. Together they form a unique fingerprint.

Cite this