| dc.contributor.author | Weller, Daniel Stuart | |
| dc.contributor.author | Goyal, Vivek K. | |
| dc.date.accessioned | 2012-07-25T16:13:47Z | |
| dc.date.available | 2012-07-25T16:13:47Z | |
| dc.date.issued | 2009-05 | |
| dc.date.submitted | 2009-04 | |
| dc.identifier.issn | 1520-6149 | |
| dc.identifier.issn | 978-1-4244-2354-5 | |
| dc.identifier.issn | 978-1-4244-2353-8 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/71801 | |
| dc.description.abstract | Sampling error due to jitter, or noise in the sample times, affects the precision of analog-to-digital converters in a significant, nonlinear fashion. In this paper, a polynomial least squares (PLS) estimator is derived for an observation model incorporating both independent jitter and additive noise, as an alternative to the linear least squares (LLS) estimator. After deriving this estimator, its implementation is discussed, and it is simulated using Matlab. In simulations, the PLS estimator is shown to improve the mean squared error performance by up to 30 percent versus the optimal linear estimator. | en_US |
| dc.description.sponsorship | National Defense Science and Engineering Graduate Fellowship | en_US |
| dc.description.sponsorship | National Science Foundation (U.S.) (Career Grant CCF-0643836) | en_US |
| dc.description.sponsorship | Texas Instruments Leadership University Consortium Program | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1109/ICASSP.2009.4960340 | en_US |
| dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
| dc.source | IEEE | en_US |
| dc.title | Jitter compensation in sampling via polynomial least squares estimation | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Weller, Daniel S., and Vivek K. Goyal. “Jitter Compensation in Sampling via Polynomial Least Squares Estimation.” IEEE, 2009. 3341–3344. © Copyright 2009 IEEE | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Research Laboratory of Electronics | en_US |
| dc.contributor.approver | Goyal, Vivek K. | |
| dc.contributor.mitauthor | Weller, Daniel Stuart | |
| dc.contributor.mitauthor | Goyal, Vivek K. | |
| dc.relation.journal | Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2009 | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| dspace.orderedauthors | Weller, Daniel S.; Goyal, Vivek K. | en |
| mit.license | PUBLISHER_POLICY | en_US |
| mit.metadata.status | Complete | |
