Synthetic software tool for compressive sensing reconstruction

Abstract

A synthetic software tool for the reconstruction of Compressive Sensed signals is proposed. Compressive Sensing is a new signal sensing approach aiming to decrease the requirements for resources in real digital systems. Using very complex mathematical algorithms, it is possible to reconstruct the Compressive Sensed signals using just a small number of randomly chosen samples. Accordingly, the proposed software comprises and implements different signal reconstruction algorithms, providing different reconstruction performances. There is also an open possibility to include other methods within the software. Here, we will present just some of the most important algorithms and functionalities provided by the proposed tool. The software options and efficiency will be demonstrated on synthetic and real-world signals.