MATLAB
Cluster analysis, which focuses on the grouping and categorization of similar elements, is widely used in various fields of research. Inspired by the phenomenon of atomic fission, this paper proposes a novel density-based clustering algorithm, called fission clustering (FC). It focuses on mining the dense families of clusters in the dataset and utilizes the information of the distance matrix to fissure the dataset into subsets.
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The dataset contains PMU measurements of all ten generators of IEEE 39-bus transmission system model, installed at the generators terminal. The dataset was obtained by using RTDS power system simulator and GTNETx2 based PMUs, and was stored by using Synchro-measurement Application Development Framework (SADF) Matlab library. Dataset constructs in total 86.6s of simulation and 5197 PMU measurements per generator.
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5102 Views
This dataset contains the full set of experimental waveforms that were used to produce the article "Non-Linear Phase Noise Mitigation over Systems using Constellation Shaping", published in the Journal of Lightwave Technology with DOI: 10.1109/JLT.2019.2917308.
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407 Views
A VOR receiver based on Software-Defined Radio is presented. Experiments showed that the system indicated the radials of the VOR station of São José dos Campos with an average error rate of less than 1% and a standard deviation of less than 2.14% in relation to those calculated cartographically. The results suggest that low volume and weight SDR-based VOR receivers can be developed with processing on microcontrollers or FPGAs to equip drones that need to operate in aerodrome environments.
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1008 Views
The MATLAB program provides the performance of a sliding window based detection for a pulse radar signal.
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856 Views
The MATLAB program provides the performance of a sliding window based detection for a pulse radar signal.
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520 Views
High-fidelity, physics-based multichannel radar data cube provided by the DARPA KASSPER project. This data is ideal for analyzing space-time adaptive processing (STAP) algorithms since both sample data and truth data are provided.
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2656 Views
Speech detection systems are known as a type of audio classifier systems which are used to recognize, detect or mark parts of audio signal including human speech. Here, a novel robust feature named Long-Term Spectral Pseudo-Entropy (LTSPE) is proposed to detect speech and its purpose is to improve performance in combination with other features, increase accuracy and to have acceptable performance. Experimental results show that if LTSPE is combined with other features, performance of the detector is improved.
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504 Views