Results 221 to 230 of about 3,104,277 (280)

A Calibrated Multi-Dimensional Evaluation Framework for Diffusion-Based Radio Frequency Signal Generation. [PDF]

Sensors (Basel)
Li Q, Xiang X, Liang Y, Mao H.
europepmc   +1 more source

DGrA: Lightweight Modulation Recognition Based on Hybrid Neural Networks. [PDF]

Sensors (Basel)
Chen X, Gao R, Xu D, Zhu H.
europepmc   +1 more source

Clinical application of artificial intelligence technology in epilepsy. [PDF]

Acta Epileptol
Ren Q, Zhang Y, Deng X, Fu M, Li X, Wang L, Chen X, Yang Y, Zhang J.   +8 more
europepmc   +1 more source

CAIC-Net: Robust Radio Modulation Classification via Unified Dynamic Cross-Attention and Cross-Signal-to-Noise Ratio Contrastive Learning. [PDF]

Sensors (Basel)
Wu T, Zhu Q, Mao R, Hu C, Wei S.
europepmc   +1 more source

Automatic Modulation Classification with Deep Neural Networks

Electronics, 2023
Automatic modulation classification is an important component in many modern aeronautical communication systems to achieve efficient spectrum usage in congested wireless environments and other communications systems applications. In recent years, numerous convolutional deep learning architectures have been proposed for automatically classifying the ...
Larson Eric, Mitchell A. Thornton, Clayton Harper   +2 more
exaly   +5 more sources

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Comparison of Automatic Modulation Classification Techniques

Journal of Communications, 2022
The advancement of digital communication and technology triggered new challenges related to the channel and radio spectrum utilization. From the other hand, real-time communications are keen of time where requests need to be processed in very short time.
Salah Ayad Jassim, Ibrahim Khider
openaire   +1 more source

A comparison of clustering algorithms for automatic modulation classification

Expert Systems With Applications, 2020
Abstract In this paper, the k-means, k-medoids, fuzzy c-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Ordering Points To Identify the Clustering Structure (OPTICS), and hierarchical clustering algorithms (with the addition of the elbow method) are examined for the purpose of Automatic Modulation Classification (AMC ...
Melvin Ferreira, Jacques Mouton
exaly   +2 more sources

Automatic Modulation Classification using DenseNet

2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP), 2021
Wireless Communication over long distances has revolutionised the way world works, functions and interacts.Modulation of a signal containing information has made all this possible.The identification of modulation type of a signal forms an integral part in several military and civilian applications.While the classical approaches of modulation ...
Sameera Shaik, S. Kirthiga
openaire   +1 more source

LSTM-based Automatic Modulation Classification

2020 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), 2020
Recently, automatic modulation classification (AMC) has been studied by more and more researchers, and a host of methods based on deep learning have been proposed. Different from image data, signal data is a sequence that changes with time, and has temporal characteristics. Like the spatial feature, the temporal feature cannot be ignored. In this paper,
Quan Zhou 0008, Xiaojun Jing, Yuan He 0009, Yuanhao Cui, Michel Kadoch, Mohamed Cheriet   +5 more
openaire   +2 more sources