RF Dataset of Incumbent Radar Signals in the 3.5 GHz CBRS Band
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| Vydáno v: | Journal of Research of the National Institute of Standards and Technology vol. 124 (2019), p. 1 |
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| 024 | 7 | |a 10.6028/jres.124.038. |2 doi | |
| 035 | |a 2330956190 | ||
| 045 | 2 | |b d20190101 |b d20191231 | |
| 084 | |a 18898 |2 nlm | ||
| 100 | 1 | |a Caromi, Raied | |
| 245 | 1 | |a RF Dataset of Incumbent Radar Signals in the 3.5 GHz CBRS Band | |
| 260 | |b Superintendent of Documents |c 2019 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a In addition to test accuracy, receiver operating characteristic (ROC) curves are of interest for evaluating detection performance. [...]we chose a relatively large number of waveforms for the dataset in order to provide enough test points per SNR value to generate ROC curves. The National Institute of Standards and Technology is an agency of the U.S. Department of Commerce. 1Certain commercial equipment, instruments, or materials are identified in this paper to foster understanding. [2] Sanders FH, Carroll JE, Sanders GA, Sole RL, Devereux JS, Drocella EF (2017) Procedures for laboratory testing of environmental sensing capability sensor devices (National Telecommunications and Information Administration, Boulder, CO), Technical Memorandum TM 18-527. | |
| 610 | 4 | |a Department of Commerce National Telecommunications & Information Administration National Institute of Standards & Technology | |
| 651 | 4 | |a United States--US | |
| 653 | |a Wireless networks | ||
| 653 | |a Waveforms | ||
| 653 | |a Datasets | ||
| 653 | |a Deep learning | ||
| 653 | |a Federal agencies | ||
| 653 | |a Laboratory tests | ||
| 653 | |a Signal processing | ||
| 653 | |a Noise | ||
| 653 | |a Algorithms | ||
| 653 | |a Environmental testing | ||
| 653 | |a Radar systems | ||
| 653 | |a Data dictionaries | ||
| 653 | |a Machine learning | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Laboratories | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Souryal, Michael | |
| 700 | 1 | |a Hall, Timothy A | |
| 773 | 0 | |t Journal of Research of the National Institute of Standards and Technology |g vol. 124 (2019), p. 1 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2330956190/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2330956190/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2330956190/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |