Title :
A rakeness-based design flow for Analog-to-Information conversion by Compressive Sensing
Author :
Cambareri, Valerio ; Mangia, Mauro ; Pareschi, Fabio ; Rovatti, Riccardo ; Setti, Gianluca
Author_Institution :
ARCES, Univ. of Bologna, Bologna, Italy
Abstract :
Classical design of Analog-to-Information converters based on Compressive Sensing uses random projection matrices made of independent and identically distributed entries. Leveraging on previous work, we define a complete and extremely simple design flow that quantifies the statistical dependencies in projection matrices allowing the exploitation of non-uniformities in the distribution of the energy of the input signal. The energy-driven reconstruction concept and the effect of this design technique are justified and demonstrated by simulations reporting conspicuous savings in the number of measurements needed for signal reconstruction that approach 50%.
Keywords :
compressed sensing; matrix algebra; signal reconstruction; analog-to-information conversion; analog-to-information converters; compressive sensing; energy-driven reconstruction concept; independent-identically distributed entries; rakeness-based design flow; random projection matrices; signal energy distribution; signal reconstruction; statistical dependency; Circuits and systems; Compressed sensing; Correlation; Eigenvalues and eigenfunctions; Energy measurement; Optimization; Vectors;
Conference_Titel :
Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-5760-9
DOI :
10.1109/ISCAS.2013.6572107