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Proceedings Paper

Asynchronous signal-dependent non-uniform sampler
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Paper Abstract

Analog sparse signals resulting from biomedical and sensing network applications are typically non–stationary with frequency–varying spectra. By ignoring that the maximum frequency of their spectra is changing, uniform sampling of sparse signals collects unnecessary samples in quiescent segments of the signal. A more appropriate sampling approach would be signal–dependent. Moreover, in many of these applications power consumption and analog processing are issues of great importance that need to be considered. In this paper we present a signal dependent non–uniform sampler that uses a Modified Asynchronous Sigma Delta Modulator which consumes low–power and can be processed using analog procedures. Using Prolate Spheroidal Wave Functions (PSWF) interpolation of the original signal is performed, thus giving an asynchronous analog to digital and digital to analog conversion. Stable solutions are obtained by using modulated PSWFs functions. The advantage of the adapted asynchronous sampler is that range of frequencies of the sparse signal is taken into account avoiding aliasing. Moreover, it requires saving only the zero–crossing times of the non–uniform samples, or their differences, and the reconstruction can be done using their quantized values and a PSWF–based interpolation. The range of frequencies analyzed can be changed and the sampler can be implemented as a bank of filters for unknown range of frequencies. The performance of the proposed algorithm is illustrated with an electroencephalogram (EEG) signal.

Paper Details

Date Published: 23 May 2014
PDF: 10 pages
Proc. SPIE 9109, Compressive Sensing III, 910907 (23 May 2014); doi: 10.1117/12.2050568
Show Author Affiliations
Azime Can-Cimino, Univ. of Pittsburgh (United States)
Luis F. Chaparro, Univ. of Pittsburgh (United States)
Ervin Sejdić, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 9109:
Compressive Sensing III
Fauzia Ahmad, Editor(s)

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