Advanced metering the signal activity of combined signal in sparse data condition
Wen-Hui Lo, Sin‐Horng Chen · 2011
The performance of finding the upper bound of eigenvalues (UBE) is affected by the quality of correlation matrix estimation. In this paper, a new quantile-based maximum likelihood mean estimator is proposed to improve the mean estimation on sparse data condition so as to obtain a more reliable correlation matrix estimate from observed samples. This in turn improves the UBE finding. The study is specially focused on the quasi-normal signal of combined quantities with asymptotic window-shape distribution and fast-decaying short tail. Experimental results show that the new mean estimator outperforms the conventional sample mean estimator on mean estimation. The UBE finding is also improved accordingly.