Automatic modulation classification using ResNeXt-GRU with deep feature fusion
With the integrated design and application of radar, communication, and electronic
reconnaissance, automatic modulation classification (AMC) is becoming increasingly …
reconnaissance, automatic modulation classification (AMC) is becoming increasingly …
Numerical and approximate solutions for coupled time fractional nonlinear evolutions equations via reduced differential transform method
We construct an explicit and approximate solutions of fractional time-nonlinear fractional
equations by using a new approach, namely, the reduced differential transform (RDTM) …
equations by using a new approach, namely, the reduced differential transform (RDTM) …
Modulation-constrained clustering approach to blind modulation classification for MIMO systems
Blind modulation classification is a fundamental step before signal detection in cognitive
radio networks where the knowledge of modulation scheme is not completely known. In this …
radio networks where the knowledge of modulation scheme is not completely known. In this …
Graphic constellations and DBN based automatic modulation classification
In this paper, we propose a low-complexity graphic constellation projection (GCP) algorithm
for automatic modulation classification (AMC), where the recovered symbols are projected …
for automatic modulation classification (AMC), where the recovered symbols are projected …
Automatic modulation classification: Cauchy-Score-function-based cyclic correlation spectrum and FC-MLP under mixed noise and fading channels
S Luan, Y Gao, T Liu, J Li, Z Zhang - Digital Signal Processing, 2022 - Elsevier
Automatic modulation classification (AMC), also termed blind signal modulation recognition,
plays a critical role in various civilian and military applications. Although existing …
plays a critical role in various civilian and military applications. Although existing …
Low-complexity deep learning and RBFN architectures for modulation classification of space-time block-code (STBC)-MIMO systems
MH Shah, X Dang - Digital Signal Processing, 2020 - Elsevier
Due to the constraint of spectrum availability in the recent era, technologies such as
cognitive radio and spectrum sensing have found a central stage in the communications …
cognitive radio and spectrum sensing have found a central stage in the communications …
Automatic modulation classification using KELM with joint features of CNN and LBP
C Hou, Y Li, X Chen, J Zhang - Physical Communication, 2021 - Elsevier
Signal automatic modulation classification refers to modulation methods which can
automatically classify and identify different communication signals. As the middle part of the …
automatically classify and identify different communication signals. As the middle part of the …
[HTML][HTML] A novel method for feature learning and network intrusion classification
With the rapid advancement in technology, network systems are becoming prone to more
sophisticated types of intrusions. However, machine learning (ML) based strategies are …
sophisticated types of intrusions. However, machine learning (ML) based strategies are …
Mobile signal modulation recognition based on multimodal feature fusion
Z Cai, Y Li, Q Wu - Mobile Networks and Applications, 2022 - Springer
In mobile communication, automatic modulation recognition of mobile signals has always
attracted attention. In the more and more complex electronic environment, the researchers …
attracted attention. In the more and more complex electronic environment, the researchers …
PSK/QAM modulation recognition by convolutional neural network
In this paper, we propose an algorithm to extract a one-dimensional (1D) non-intuitive
feature of the received signal for automatic modulation classification (AMC). This designed …
feature of the received signal for automatic modulation classification (AMC). This designed …