Over the years, I've encountered many engineers (a majority in fact) who are still puzzled by the subtleties of sampling. Even though they may know some mathematical basics, or have some idea of how ...

Sampling operators constitute a class of linear and nonlinear mappings designed to reconstruct or approximate functions from discrete data. Rooted in classical Shannon theory, modern developments ...

This repository implements the three main experiments from “A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive” and provides utilities to reproduce the paper’s ...

Abstract: Multidimensional stochastic sampling is crucial for many applications that rely on the reconstruction of spatial fields from observations gathered by distributed sensing devices, including ...

Abstract: In this letter, we propose a general partial arc orthogonal receiving (GPAOR) theory based on the electromagnetic information theory for orbital angular momentum (OAM) orthogonal ...