Implementation models for analog-to-information conversion via random sampling

Tamer Ragheb, Sami Kirolos, Jason Laska, Anna Gilbert, Martin Strauss, Richard Baraniuk, Yehia Massoud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

71 Scopus citations

Abstract

We develop a framework for analog-to-information conversion based on the theory of information recovery from random samples. The framework enables sub-Nyquist acquisition and processing of wideband signals that are sparse in a local Fourier representation. We present the random sampling theory associated with an efficient information recovery algorithm to compute the spectrogram of the signal. Additionally, we develop a hardware design for the random sampling system that demonstrates a consistent reconstruction fidelity in the presence of sampling jitter, which forms the main source of non-ideality in a practical system implementation. ©2007 IEEE.
Original languageEnglish (US)
Title of host publicationMidwest Symposium on Circuits and Systems
Pages325-328
Number of pages4
DOIs
StatePublished - Dec 1 2007
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-13

Fingerprint

Dive into the research topics of 'Implementation models for analog-to-information conversion via random sampling'. Together they form a unique fingerprint.

Cite this