Outlier detection on power consumption via non-negative tensor factorization models.

Missing data and outliers are encountered frequently in signal processing problems. Presence of outliers can reduce the performance in completion of missing values or interpolation. In this work, we present a method based on Non-negative Tensor Factoriazation models that is able to solve interpolation and finding consuming characteristics problems on electrical power consumption data with high performance.