Digital signal processing

In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve as a reference for quality assessment. As a result, full-reference (FR) and reduced-reference (RR) image quality assessment (IQA) methods are generally infeasible. Although no-reference (NR) methods are readily applicable, their performance is often not reliable.

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In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve as a reference for quality assessment. As a result, full-reference (FR) and reduced-reference (RR) image quality assessment (IQA) methods are generally infeasible. Although no-reference (NR) methods are readily applicable, their performance is often not reliable.

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In this dataset, we provided the raw analog-to-digital-converter (ADC) data of a 77GHz mmwave radar for the carry object detection scenario. The overall dataset contains approximately 3000 frames of radar data as well as synchronized camera images and labels. For each radar frame, its raw data has 4 dimensions: samples (fast time), chirps (slow time), transmitters, and receivers. The experiment radar was assembled from the TI cascaded-chip TIDEP-01012 board, with 12 transmit antennas and 16 receive antennas.

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Five users aged 23, 25, 31, 42, and 46 participated in the experiment. The users sat comfortably in a chair. A green LED of 1 cm diameter was placed at a distance of about 1 meter from a person's eyes. EEG signals were recorded using g.USBAmp with 16 active electrodes. The users were stimulated with flickering LED lights with frequencies: 5 Hz, 6 Hz, 7 Hz, and 8 Hz. The stimulation lasted 30 seconds. The recorded signals were divided into the data used for training, the first 20 seconds, and the data used for testing, the next 10 seconds, for each signal.

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The Research Paper "Detection of Bicep Form Using Myoware and Machine Learning" based on the novel dataset has been recently accepted in September 2022 and is being published in SCOPUS Indexed SPRINGER Book Series “Lecture Notes in Networks and Systems”

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1077 Views

This data set provides complex-baseband samples of vehicle-to-vehicle communication (V2V) radios in the presence of primitive jamming signals. Up to 600 vehicles are simulated in this dataset using commerical IEEE 802.11p radios. Supporting example code found on CodeOcean can be used for developing novel physical layer based jamming detection and mitigation strategies using machine learning for ad hoc vehicular networks.

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A real-world radio frequency (RF) fingerprinting dataset for commercial off-the-shelf (COTS) Bluetooth and WiFi emitters under challenging testbed setups is presented in this dataset. The chipsets within the devices (2 laptops and 8 commercial chips) are WiFi-Bluetooth combo transceivers. The emissions are captured with a National Instruments Ettus USRP X300 radio outfitted with a UBX160 daughterboard and a VERT2450 antenna. The receiver is tuned to record a 66.67 MHz bandwidth of the spectrum centered at the 2.414 GHz frequency.

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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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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

Matlab design scripts and simulink simulation files for 3 example designs for Design of Stable Digital Non-Foster Impedances for Electrically-Small Antennas Beyond The Chu Limit.

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