Title :
Comparison of synthesis-based and analysis-based compressive sensing
Author :
Oey Endra;Dadang Gunawan
Author_Institution :
Wireless and Signal Processing (WASP), Department of Electrical Engineering, Universitas Indonesia, Depok, 16424, Indonesia
Abstract :
The synthesis sparse representation model of signals regards that signal is formed from linear combination of a few atoms from a synthesis dictionary. Compressive sensing (CS) as a novel technique to acquire the signal directly in already compressed is based on that model. The analysis sparse representation as alternative model for the signals began to gain attention in recent years. The sparse analysis coefficients are obtained in analysis model by multiplying analysis dictionary and the signal. In this paper, we compare the performance of synthesis-based and analysis-based CS system. The simulation results show that analyisis-based CS provides better performance than synthesis-based CS in terms of signal recovery accuracy. It suggests that the analyis model will play an important role in the future direction of the CS research.
Keywords :
"Analytical models","Dictionaries","Sensors","Compressed sensing","Sparse matrices","Simulation","Matching pursuit algorithms"
Conference_Titel :
Quality in Research (QiR), 2015 International Conference on
Print_ISBN :
978-1-4799-6550-2
DOI :
10.1109/QiR.2015.7374920