MOSAICS: Multiplexed Optimal Signal Acquisition Involving Compressed Sensing

Satyanarayana, JV and Ramakrishnan, AG (2010) MOSAICS: Multiplexed Optimal Signal Acquisition Involving Compressed Sensing. In: International Conference on Signal Processing and Communications, JUL 18-21, 2010, Indian Inst Sci, Bangalore, INDIA.

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Abstract

It is possible to sample signals at sub-Nyquist rate and still be able to reconstruct them with reasonable accuracy provided they exhibit local Fourier sparsity. Underdetermined systems of equations, which arise out of undersampling, have been solved to yield sparse solutions using compressed sensing algorithms. In this paper, we propose a framework for real time sampling of multiple analog channels with a single A/D converter achieving higher effective sampling rate. Signal reconstruction from noisy measurements on two different synthetic signals has been presented. A scheme of implementing the algorithm in hardware has also been suggested.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright 2010 IEEE. Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords:	A/D Conversion; Nyquist sampling theorem; Bandlimited signals; Fourier sparsity; Real time; Data acquisition; Compressed Sensing; Monopulse radar
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	06 Apr 2011 10:28
Last Modified:	06 Apr 2011 10:28
URI:	http://eprints.iisc.ac.in/id/eprint/36376

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