The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
More Is Less: Signal Processing and the Data Deluge
Abstract
The data deluge is changing the operating environment of many sensing systems from data-poor to data-rich––so data-rich that we are in jeopardy of being overwhelmed. Managing and exploiting the data deluge require a reinvention of sensor system design and signal processing theory. The potential pay-offs are huge, as the resulting sensor systems will enable radically new information technologies and powerful new tools for scientific discovery.
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Cites
A Global Geometric Framework for Nonlinear Dimensionality Reduction
Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585
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Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing
Everton, S. K., Hirsch, M., Stravroulakis, P., Leach, R. K., & Clare, A. T. (2016) · Materials & Design · doi:10.1016/j.matdes.2016.01.099 · Cited by 1,469
Tsai, C.-W., Lai, C.-F., Chao, H.-C., & Vasilakos, A. V. (2015) · Journal of Big Data · doi:10.1186/s40537-015-0030-3 · Cited by 818
Hou, R., & Xia, Y. (2021) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2020.115741 · Cited by 674
Data Mining for Internet of Things: A Survey
Tsai, C.-W., Lai, C.-F., Chiang, M.-C., & Yang, L. T. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.103013.00206 · Cited by 620
Compressive Sensing in Electromagnetics - A Review
Massa, A., Rocca, P., & Oliveri, G. (2015) · IEEE Antennas and Propagation Magazine · doi:10.1109/map.2015.2397092 · Cited by 360
Metadata
- Authors
- Baraniuk, R. G.
- Venue
- Science
- Published
- 2011-02-11
- Volume
- 331
- Issue
- 6018
- Pages
- 717-719
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2051061727
- Cited by
- 240
- References
- 1
- FWCI
- 34.17
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
