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Double shrinkage correction in sample LMMSE estimation
Serra, Jordi; Nájar Martón, Montserrat
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
The sample linear minimum mean square error (LMMSE) es- timator undergoes high performance degradation in the small sample size regime. Herein a double shrinkage correction is proposed to alleviate this problem. First, an af ne transfor- mation of the sample covariance matrix (SCM) is considered within the LMMSE. Second, a linear transformation of that modi ed lter is proposed. The linear transformation mini- mizes the asymptotic MSE of the lter given a shrinkage of the SCM. And the shrinkage of the SCM optimizes the as- ymptotic MSE of the data covariance. Simulations highlight that the proposed estimator outperforms robust methods to the small sample size, namely LMMSE based on diagonal load- ing (DL) or Ledoit-Wolf (LW) regularizations of the SCM
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament del senyal en les telecomunicacions
Signal processing
LMMSE
Shrinkage
Small sample size
Random matrix theory
Tractament del senyal
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
European Association for Signal Processing (EURASIP)
         

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