Title :
Asynchronous sampling and reconstruction of sparse signals
Author :
Azime Can;Ervin Sejdic;Luis Chaparro
Author_Institution :
Department of Electrical and Computer Engineering, 1140 Benedum Hall, University of Pittsburgh, Pittsburgh, PA, 15261, USA
Abstract :
Asynchronous signal processing is an appropriate low-power approach for the processing of bursty signals typical in biomedical applications and sensing networks. Different from the synchronous processing, based on the Shannon-Nyquist sampling theory, asynchronous processing is free of aliasing constrains and quantization error, while allowing continuous-time processing. In this paper we connect level-crossing sampling with time-encoding using asynchronous sigma delta modulators, to develop an asynchronous decomposition procedure similar to the Haar transform wavelet decomposition. Our procedure provides a way to reconstruct bounded signals, not necessarily band-limited, from related zero-crossings, and it is especially applicable to decompose sparse signals in time and to denoise them. Actual and synthetic signals are used to illustrate the advantages of the decomposer.
Keywords :
"Quantization","Approximation methods","Signal to noise ratio","Sigma delta modulation","Modulation"
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
Print_ISBN :
978-1-4673-1068-0
Electronic_ISBN :
2076-1465