Automatic modulation classification facilitates many important signal processing
applications. Recently, deep learning models have been adopted in modulation recognition …

Recently, deep learning has received a lot of attention in many machine learning
applications for its superior classification performance in speech recognition, natural …

Automatic modulation recognition (AMR) is a promising technology for intelligent
communication receivers to detect signal modulation schemes. Recently, the emerging deep …

Deep learning has great potential for automatic modulation classification (AMC). However,
its performance largely hinges upon the availability of sufficient high-quality labeled data. In …

Automatic modulation classification (AMC) identifies a received signal's modulation scheme
without prior knowledge of the intercepted signal, which enables significant applications in …

As a backbone of deep learning models, convolutional neural networks (CNNs) are widely
used in the field of automatic modulation classification. Nevertheless, we speculate that the …

Automatic modulation classification (AMC) is to identify the modulation type of a received
signal, which plays a vital role to ensure the physical-layer security for Internet of Things …

Modulation classification is one of the key tasks for communications systems monitoring,
management, and control for addressing technical issues, including spectrum awareness …

Automatic modulation classification (AMC) is a typical technology for identifying different
modulation types, which has been widely applied into various scenarios. Recently, deep …

Deep learning has recently attracted much attention due to its excellent performance in
processing audio, image, and video data. However, few studies are devoted to the field of …