Amostragem Compressiva: Princípios Fundamentais e Aplicação com RMPI Adaptado

Hugo B. S. Araujo; Rubens M. B. da S. Lima; Adna Kallery Santos da Silva; Cleonilson P. de Souza

doi:10.20906/CBA2022/3627

Hugo B. S. Araujo Universidade Federal da Paraiba, PB
Rubens M. B. da S. Lima Universidade Federal da Paraiba, PB
Adna Kallery Santos da Silva Universidade Federal da Paraiba, PB
Cleonilson P. de Souza Universidade Federal da Paraiba, PB

DOI: https://doi.org/10.20906/CBA2022/3627

Keywords: Compressed Sensing, Analog-to-Information Converter, Sparsity

Abstract

Compressed Sensing (CS) is a technique that takes advantage of signal sparsity in a given domain and allows sampling with sub-Nyquist sampling rates. A device that implements the CS model is the Analog-to-Information Converter (AIC), which obtains an output that is a digitized and compressed version of the input. This paper presents CS principles, analysis, and results obtained for a dual-tone sine signal applied to a version of a Random Modulation Pre-Integrator (RMPI) AIC.