**.mat
This letter presents a novel approach to bolster the physical layer security of optical communication systems, specifically within Passive Optical Networks (PONs), through the utilization of device fingerprints. In this proposed scheme, we employ Optical On-Off Keying (OOK) modulation for signal transmission and subsequently extract distinct fingerprint features from the eye diagrams of these OOK signals. These fingerprint features are then subjected to dimensionality reduction via Siamese neural networks.
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This dataset is recorded by 26 subjects in Shandong Provincial Hospital using wearable ECG devices. It totally includes 208 segments with a duration of 30 seconds. The sampling rate is 256Hz. All the data format is ‘.mat’. This dataset can be used for signal quality assessment as the unacceptable category. All the data are recorded in free-living conditions with various noises. This dataset is recorded by 26 subjects in Shandong Provincial Hospital using wearable ECG devices. It totally includes 208 segments with a duration of 30 seconds. The sampling rate is 256Hz.
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A 5.76-second piano rendition of the Inspector Gadget Theme with a sampling rate of 44.1 kHz, played 2 mm from the multi-mode fiber. High-speed infrared camera data, derived from sound sampled at 1.93 kHz, consists of 10,000 frames capturing vibrations on a multi-mode fiber. It includes 128*8 pixel data and can be monitored, played, and processed through MATLAB.
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This LTE_RFFI project sets up an LTE device radio frequency fingerprint identification system using deep learning techniques. The LTE uplink signals are collected from ten different LTE devices using a USRP N210 in different locations. The sampling rate of the USRP is 25 MHz. The received signal is resampled to 30.72 MHz in Matlab. Then, the signals are processed and saved in the MAT file form. More details about the datasets can be found in the README document.
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Modern, industrial use cases for wireless communications are related to mobile applications such as moving robotics in industrial environments. For the design of communication systems, the behavior of the radio channel, especially over time, is of great importance. Most of the existing data sets for industrial radio channels originate from static measurement procedures, containing an arbitrary subset of the environment.
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620 Views
This LTE_RFFI project sets up an LTE device radio frequency fingerprint identification system using deep learning techniques. The LTE uplink signals are collected from ten different LTE devices using a USRP N210 in different locations. The sampling rate of the USRP is 25 MHz. The received signal is resampled to 30.72 MHz in Matlab and is saved in the MAT file form. The corresponding processed signals are included in the dataset. More details about the datasets can be found in the README document.
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467 Views
Dataset description:
This contains ten categories of gas data, each category contains 5 concentrations, 10, 20, 30, 40, 50ppm.
There are 160 groups of 10, 20, 30, 40, each group contains 6000 sampled voltage signals, and the sampling frequency is 10HZ.
There are only 80 groups for 50ppm concentration, and each group also contains 6000 sampled voltage signals.
The label corresponding to each gas includes category and concentration, which can be split by gas category and concentration.
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1316 Views
Los datos empleados en el análisis del estudio fueron obtenidos del sistema SAP del Departamento Comercial de la Compañía Nacional de Electricidad (CNEL EP) Unidad de Negocio Esmeraldas. Estos datos consisten en registros originales de consumo mensual de energía eléctrica facturada (expresada en kilovatios-hora, kWh) durante un periodo de 25 meses (enero de 2021 a enero 2023). Estos registros pertenecen a 136218 clientes aproximadamente de del sector residencial de la provincia de Esmeraldas.
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620 Views
This data set is the data of the studies carried out in the article named "BalanSENS: Robotic platform system for balance analysis, rehabilitation and assistance with feedforward and feedback signals". BalanSENS is devised to embrace an approach that promotes active engagement by amalgamating diverse sensory inputs to enhance both sensory and motor functions. Its capacity to personalize balance rehabilitation for each individual is accomplished through a three-phase framework. The attributes of the servo motors are assessed to demonstrate their suitability for I-BaR.
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In data file (.rar) contains 16 files in .mat format, where origin data after UMAP for training.mat is the original training data and the others are the experimental result data. data1_*.mat is the model test result file containing the simulation results (test_simu_*), model output (output_test_*), and error (error_*).
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