Title :
Polynomial LMMSE estimation: A case study
Author :
Uhlich, Stefan ; Loesch, Benedikt ; Bin Yang
Author_Institution :
Syst. Theor. & Signal Process., Univ. Stuttgart, Stuttgart, Germany
Abstract :
This paper investigates the potential of the polynomial LMMSE estimation for nonlinear/nongaussian estimation problems. This is done by a case study: the estimation of the frequency of a sinusoidal signal with unknown amplitude and phase. We give analytical formulas to calculate the second order moments which are needed for the polynomial LMMSE estimation and we study the performance for varying orders of observations. Variable selection is used to identify the most relevant observations. It turns out that only a small number (less than one percent) of all available variables gives nearly the same mean squared error.
Keywords :
frequency estimation; least mean squares methods; frequency estimation; linear minimum mean squared error; polynomial LMMSE estimation; second order moments; sinusoidal signal; variable selection; Amplitude estimation; Computer aided software engineering; Frequency estimation; Input variables; Maximum likelihood estimation; Performance analysis; Phase estimation; Polynomials; Signal processing; Vectors; Frequency estimation; Linear MMSE estimation; Variable selection;
Conference_Titel :
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location :
Cardiff
Print_ISBN :
978-1-4244-2709-3
Electronic_ISBN :
978-1-4244-2711-6
DOI :
10.1109/SSP.2009.5278637
