Advanced metering the signal activity of combined signal in sparse data condition

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.