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25 results for “SNR”
differential dust extinction towards SNR RX J1713.7-3946
<p>The dataset contains 6 approximate posterior sample of differential dust extinction towards the supernova remnant RX J1713.7-3946 .</p>
Data sets for Span-level SNR Regression in EONs
<ul> <li><strong>DS1: </strong>the symbol rate is fixed and equals 64 Gbaud, and the channel loading factor is selected from [25 − 100];</li> <li><strong>DS2:</strong> the symbol rate and channel occupancy status is randomly selected (uniformly distributed) from {32, 64, 96 (GBaud) and {0, 1}, respectively;</li> <li> <strong>DS3</strong>: both symbol rate and the channel loading factor are fixed and equal to 64 GBaud and 25%, respectively.</li> </ul>
Raw SNR data for Manuscript "GPS Interferometric Reflectometry : Using a Low Cost Antenna to Measure Water Levels"
<p>Raw GPS L1 SNR (and ancillary) data for an experiment to use a low-cost GPS antenna/receiver to measure water levels using the GNSS - Interferometric Reflectometry technique.</p> <p>The data were recorded at the RNLI lifeboat station in Sligo, Ireland (N 54<sup>o </sup>18' 17.8'', W 8<sup>o</sup> 34' 5.4'' ) using a Globalsat BU353S4 USB puck that uses a SirfStar IV receiver with patch antenna (2018 data) and a Maestro A2200A SirfStar IV module (2019 data). Both systems were mounted to a radio mast at around 16m above sea level.</p> <p>The data are stored in daily files with the naming convention sligDDD0.YY.TNR.gz where DDD is the Day of Year and YY is the year in short format (18,19). Each file is gzipped. </p> <p>The files are flat text files with fixed width columns in the following order</p> <p>1) PRN GPS satellite code</p> <p>2) Elevation (degrees)</p> <p>3) Azimuth (degrees)</p> <p>4) Seconds of Day</p> <p>5) change in elevation angle with time (degrees/second) : needed for reflector height change corrections</p> <p>6) Blank</p> <p>7) S1 SNR signal (dB-Hz)</p> <p>8) Blank reserved for S2 SNR signal</p> <p>9) Blank reserved for S5 SNR signal</p>
Data Sets for SNR Estimation in Flexible Optical Networks: Lightpath, Link, and Span Levels
<p>These data sets have been generated based on the analytic models [1,2] to estimate signal to the noise ratio (SNR) for spans, links, and lightpaths of a Flexible Optical Network (FON) over standard single-mode fiber (SSMF). For PM-BPSK and PM-QPSK modulation format levels, equation 41-43 [1], and for PM-8-64QAM modulation format levels, equation 7.32 [2], are applied.</p> <p>[1] P. Poggiolini, G. Bosco, A. Carena, V. Curri, Y. Jiang and F. Forghieri, "The GN-Model of Fiber Non-Linear Propagation and its Applications," in <em>Journal of Lightwave Technology</em>, vol. 32, no. 4, pp. 694-721, Feb.15, 2014, DOI: 10.1109/JLT.2013.2295208.</p> <p>[2] P. Poggiolini, Y. Jiang, A. Carena and F. Forghieri, "Analytical modeling of the impact of fiber non-linear propagation on coherent systems and networks" in Enabling Technologies for High Spectral-Efficiency Coherent Optical Communication Networks, New York, NY, USA:Wiley, pp. 247-310, 2016.</p>
Colombia. Justicia. SNR Superintendencia de Notariado y Registro. Actividad Registral y Notarial 2011 a 2022,. Mensual
<p>Colombia. Justicia. SNR Superintendencia de Notariado y Registro. Actividad Registral y Notarial 2011 a 2022</p>
Temporal SNR optimization through RF coil combination in fMRI: The more, the better? - DATASET
Open the record for dataset details and reuse information.
Dataset for the manuscript: Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy
<p>These are the data files used to generate the figures in the paper: Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy. DOI: 10.1101/2023.06.27.546748</p>
Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography
<p>This repository contains the raw K-space data and all MATLAB (The MathWorks, Natick, MA) code used for reconstruction, simulations, data analysis, and figure generation used in the article titled "Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography".</p> <p>## Referencing</p> <p>If you use any of the data or the code provided here, please cite:</p> <p>1. Woods JG, Schauman SS, Chiew M, Chappell MA, Okell TW. Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography. Magnetic Resonance in Medicine. 2023; doi:10.1002/mrm.29491<br> 2. This Zenodo repository: Joseph G. Woods, S. Sophie Schauman, Mark Chiew, Michael A. Chappell & Thomas W. Okell. (2022). Time-encoded pseudo-continuous arterial spin labeling: increasing SNR in ASL dynamic angiography [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6791097</p> <p> </p> <p>If you use the reconstruction code provided here, please also cite:</p> <p>1. Fessler JA, Sutton BP. Nonuniform fast fourier transforms using min-max interpolation. IEEE Transactions on Signal Processing. 2003;51(2):560-574. doi:10.1109/TSP.2002.807005<br> 2. Fessler JA. Michigan Image Reconstruction Toolbox. https://web.eecs.umich.edu/~fessler/code/. Accessed February 26, 2018.<br> 3. Schauman SS. Accelerated_TEASL. https://github.com/SophieSchau/Accelerated_TEASL. Accessed October 19, 2020.<br> 4. Chiew M. MR Linear Encoding Operators. https://users.fmrib.ox.ac.uk/~mchiew/Tools.html. Accessed March 30, 2020.</p> <p>## Notes for use:</p> <p>All data processing is performed in MATLAB (tested with 2021a and 2021b on macOS 10.14 (Mojave) and 12 (Monterey))</p> <p>The "code/" and "data/" folders should be placed within the same folder. The necessary file paths within each script in "code/" will be set up automatically.</p> <p>**Note**: the file paths use "/", so would need to be manually changed for use on Windows, which uses "\" in file paths.</p> <p>- For performing full reconstruction of in vivo K-space data, **run reconalldata.m**.<br> - All code provided<br> - Uses:<br> 1. Jeff Fessler's MIRT: http://web.eecs.umich.edu/~fessler/irt/fessler.tgz<br> 2. Mark Chiew's: xfm_NUFFT.m, etc: https://users.fmrib.ox.ac.uk/~mchiew/Tools.html<br> 3. Sophie Schauman's Accelerated_TEASL: https://github.com/SophieSchau/Accelerated_TEASL</p> <p>- For plotting in-vivo data, **run figures_invivo.m**.<br> - FSL's read_avw to read in NIFTIs (but can replace this with MATLAB's in-built niftiread instead).<br> - (Install FSL from here: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation)<br> - All other code provided</p> <p>- For performing simulation and plotting results, **run figures_simulation.m**.<br> - All code provided</p> <p>- Location of specific Figure generation code:<br> - Figure 1: no code - manually made.<br> - Figure 2: figures_invivo.m<br> - Figure 3: figures_simulation.m<br> - Figure 4: figures_invivo.m<br> - Figure 5: figures_invivo.m<br> - Figure 6: figures_invivo.m<br> - Figure 7: figures_invivo.m<br> - Figure 8: figures_invivo.m<br> - Figure 9: figures_simulation.m<br> - Figure 10: figures_invivo.m<br> - Supporting Information Figure S1: figures_simulation.m<br> - Supporting Information Figure S2: figures_invivo.m<br> - Supporting Information Figure S3: figures_invivo.m<br> - Supporting Information Figure S4: figures_invivo.m<br> - Supporting Information Figure S5: figures_invivo.m<br> - Supporting Information Figure S6: figures_invivo.m<br> - Supporting Information Figure S7: figures_invivo.m<br> - Supporting Information Figure S8: figures_invivo.m<br> - Supporting Information Figure S9: figures_invivo.m<br> - Supporting Information Figure S10: figures_simulation.m</p>
GNSS deep SNR retrievals of marine atmosphere boundary layer (MABL) specific humidity
<p>This folder contains 5 prediction files ended with *_v2.h5. These files can be loaded using the provided code "prediction_data_loader.py". All variables are in their respective physical units.</p> <p>The *.tgz file contains the training and validation codes as well as sample training and validation datasets from METOP-B satellite. Please refer to the paper for details. All variables had been normalized in the training and validation datasets so no real physical meaning attached.</p> <p>Reference:</p> <p><a href="https://publications.copernicus.org/">Gong, J., Wu, D. L., Badalov, M., Ganeshan, M., and Zheng, M.: A machine-learning-based marine atmosphere boundary layer (MABL) moisture profile retrieval product from GNSS-RO deep refraction signals, Atmos. Meas. Tech., 18, 4025–4043, https://doi.org/10.5194/amt-18-4025-2025, 2025.</a></p> <p> </p> <p>POC: Jie.Gong@nasa.gov</p> <p>10/17/2024</p> <p> </p> <p>Update on 08/27/2025: The final paper has been published on AMT. Please see updated reference information above.</p> <p>--- THE END ---</p>
Relative Transfer Matrix for Low SNR Speech Separation from Noisy Sources in Reverberant Rooms
<p>This folder contains the supplementary audio files for the paper "Relative Transfer Matrix for Low SNR Speech Separation from Noisy Sources in Reverberant Rooms" submitted to <em>The Journal of the Acoustical Society of America</em>.</p>
PSFcheck ring pattern at various SNR
<p>The imaged PSFcheck pattern consists of a nanometric set of ring-like laser-written structures with a separation of 10 µm between each. The mean FWHM of these patterns was calculated to be 208 nm. A NanoImager-S microscope (ONI, Oxford Nanoimaging), equipped with a 100X 1.4 NA, oil-immersion objective (Olympus) was used to image the PSFcheck patterns in widefield fluorescence mode. Sample excitation was provided by a 561 nm laser and emission was collected with a 575-616.5 emission filter. A sCMOS sensor (Hamamatsu, Orca-0Flash4.0 V3) was used for image aquisition at 30 fps and 117 nm pixel size. </p>
Optimal SNR grids
<p>Optimal single-detector signal-to-noise ratios evaluated on a regular grid of detector frame masses and fixed distance. To be used for interpolation when calculating semi-analytical sensitivity estimates.</p>
SNR and RSSI from an urban LoRa Network
<p>The dataset contains various SNR and RSSI reading from a LoRa Network in the city of Portland, Maine. The dataset consists in a single sheet file, where each row corresponds to a specific LoRa node. Note that: i) the first row corresponds to the LoRa Gateway; ii) each row contains information over the node ID, its coordinates, the packet frequency, bandwidth, , Transmission Power, Spreading Factor, Coding Rate, SNR and RSSI.</p>
Input data for manuscript "SNR-based GNSS reflectometry for coastal sea-level altimetry – Results from the first IAG inter-comparison campaign"
<p>GNSS data collected at station GTGU for one year (2015.5-2016.5) and nearby tide gauge data.</p> <p>Note: the antenna position in the header file, expressed in global Cartesian coordinates, corresponds inadvertently to integer values of latitude, longitude, and altitude (57.0°, 11.0°, 0.0 m); non-truncated values are as follows: 57.3929549°, 11.9134886°, 40.420 m.</p>
Output data for manuscript "SNR-based GNSS reflectometry for coastal sea-level altimetry – Results from the first IAG inter-comparison campaign"
<p>GNSS-R sea level time series and ancillary information about periods with incomplete GNSS data.</p>
Variable SNR Upcalls
<p>12,000 30-second clips containing a single upcalls at specified SNR values. Original audio files come from: Simard, Y., Kirsebom, O., Frazao, F., Roy, N., Matwin, S., Giard, S. (2020). Acoustic recordings of North Atlantic right whale upcalls in the Gulf of St. Lawrence. Federated Research Data Repository. <a href="https://doi.org/10.20383/101.0241">https://doi.org/10.20383/101.0241</a></p>
Colombia. Justicia. SNR Superintendencia de Notariado y Registro. Actividad Notarial Municipal. 2012 a 2014
<p>Colombia. Justicia. SNR Superintendencia de Notariado y Registro. Actividad Notarial Municipal. 2012 a 2014</p>
Data and code for: Order-of-Magnitude SNR Improvement for High-Field EPR Spectrometers via 3D-Printed Quasioptical Sample Holders
<p>*.py and data files for publication titled "Order-of-Magnitude SNR Improvement for High-Field EPR Spectrometers via 3D-Printed Quasioptical Sample Holders"</p>
Combined Stimulation of STN and SNr for Dysphagia in Parkinson's Disease
ClinicalTrials.gov study NCT03470324. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Combined Stimulation of STN and SNr for Resistant Freezing of Gait in Parkinson's Disease
ClinicalTrials.gov study NCT02588144. IPD Sharing: Not stated. Countries: 2. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.