Variance analysis for least lp-norm estimator in mixture of generalized Gaussian noise

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

3 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)1226-1230
Journal / PublicationIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE100A
Issue number5
Publication statusPublished - 1 May 2017

Abstract

Variance analysis is an important research topic to assess the quality of estimators. In this paper, we analyze the performance of the least lp-norm estimator in the presence of mixture of generalized Gaussian (MGG) noise. In the case of known density parameters, the variance expression of the lp-norm minimizer is first derived, for the general complexvalued signal model. Since the formula is a function of p, the optimal value of p corresponding to the minimum variance is then investigated. Simulation results show the correctness of our study and the near-optimality of the lp-norm minimizer compared with Cramér-Rao lower bound.

Research Area(s)

  • Complex-valued signal, Lp-norm minimizer, Mixture of generalized Gaussian model, Variance analysis

Citation Format(s)

Variance analysis for least lp-norm estimator in mixture of generalized Gaussian noise. / Chen, Yuan; Huang, Long-Ting; Yang, Xiao Long; So, Hing Cheung.

In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E100A, No. 5, 01.05.2017, p. 1226-1230.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review