We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
Abstract. A forecasting approach based on Multi-Layer Perceptron (MLP) Artificial Neural Networks (named by the authors MULP) is proposed for the NN5 111 time series long-term, out...
The general setting of regression analysis is to identify a relationship between a response variable Y and one or several explanatory variables X by using a learning sample. In a ...
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
In this paper, we present a spherical sampling technique that can be employed to find optimal sensors for trichromatic color applications. The advantage over other optimization te...