Signal Processing

results obtained from a vehicle- to-vehicle channel measurement campaign carried out in the millimeter-wave band around a 60 GHz center frequency and with 8 GHz of bandwidth. We characterize a situation of two oncoming cars on a two-lane road in the campus of the Brno University of Technology. The measurement campaign consists of two independent runs of the vehicles. During each measurement run, we have acquired 468 CIR realizations. This gives almost 1000 CIR recordings in total

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Future mobile communication systems include millimeter wave (mmWave) frequency bands and high mobility scenarios. To learn how wave propagation and scattering effects change from classical sub 6 GHz to mmWave frequencies, measurements in both bands have to be conducted. We perform wireless channel measurements at 2.55 GHz and 25.5 GHz center frequency at velocites of 40 km/h and 100 km/h. To ensure a fair comparison between these two frequency bands, we perform repeatable measurements in a controlled environment.

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Synthetic Digitally Modulated Signal Datasets for Automatic Modulation Classification contain CSPB.ML.2018 and CSPB.ML.2022, two high-quality communication signal datasets with eight modulation types: BPSK, QPSK, 8-PSK, pi/4-DQPSK, MSK, 16-QAM, 64-QAM, and 256-QAM. There are 14,000 signals of each modulation type in each dataset for a total of 112,000 signals per dataset. The two datasets are useful for signal processing testing, neural network (NN) training, initial NN testing, and out-of-distribution NN testing as signal generation parameters differ between the two datasets.

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1.The dataset is the spectrum acquired by using 0.4/0.6-m long SHF.

2.There are 51 different pressure states from 0 MPa to 5 MPa.

3.For each pressure state, more than 130 spectra are collected.

4.In each spectrum, the value of the first row should be deleted. 

5.The first col of each spectrum is the wavelength, and the second col is the intensity.

6.The size of each spectrum is (508, 1)

 

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Here we provide the dataset containing the power measurements obtained with our RIS prototype, which were carried out in the anechoic chamber of TU Darmstadt.

The use of data here contained is intended only for research purposes.

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The Bluetooth 5.1 Core Specification brought Angle of Arrival (AoA) based Indoor Localization to the Bluetooth Standard. This feature is usually referred to as Bluetooth Direction Finding.

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A video dataset for the paper named "Analysis of ENF Signal Extraction From Videos Acquired by Rolling Shutters" submitted to IEEE Transactions on Information Forensics and Security (T-IFS) and under review.

If you used our dataset, please cite our paper as:

Jisoo Choi, Chau-Wai Wong, Hui Su, and Min Wu, "Analysis of ENF signal extraction from videos acquired by rolling shutters," submitted to IEEE Transactions on Information Forensics and Security (T-IFS), under review.

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video dataset for the paper named "Analysis of ENF Signal Extraction From Videos Acquired by Rolling Shutters"

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The dataset is intended to cover core issues pertaining to the area of a traffic optimization via RET motors inside the antenna on the mobile base station system (BSS). The principle of RET operation was already known to scientists; however, the use of a machine learning and big data provides the possibility of creation an autonomous system, which control RET system.

Last Updated On: 
Sun, 10/23/2022 - 08:50

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder with resting tremor (RT) being it's most common motor symptom. This study aimed to determine the features of wrist velocity and acceleration that can be used as objective, reliable, and sensitive detectors of RT. Forty-five healthy young adults imitated RT in both hands after observing a video of RT in a person with PD. Inertial measurement units placed on both wrists recorded the linear acceleration and angular velocity, which were used to calculate linear velocity and angular acceleration.

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