… output (SISO) systems, but DL-based AMC method is scarcely explored in the multiple-input …
a convolutional neural network (CNN)-based cooperative AMC (Co-AMC) method for the …

… classification (AMC) method is proposed for cognitive radio networks. Generally, as network
input of AMC convolutional neural networks (CNNs) images or complex signals are utilized …

… P proposed two convolutional neural network- (CNN-) based DL … machine learning classifiers
based on deep neural network … to train the network, and then the classification accuracy is …

… modulation schemes, single-carrier-based modulation … convolutional neural network (CNN)
and long-short term memory (LSTM). However, most conventional DL-based AMC methods …

… Specifically, we take the modulation constellation diagram (CD) … an advanced neural network
for modulation classification, … a number of parallel convolutional neural networks and then …

… In this study, a hybrid signal and image-based deep learning model is designed for AMC in
CR. A convolutional neural network (CNN) is applied in both the deep learning models. The …

… images to feed the input of the CNN deep learning method. In the second stage, the obtained
… Automatic modulation classification (AMC) has been an important part of many militaries, …

… target classification based on dense convolutional neural network,” … Guo, “A survey on deep
learning techniques in wireless … Mokayef, “Machine learning based automatic modulation …

… method, which combines a convolutional neural network (CNN) with the continuous wavelet
transform (CWT) for multiclass modulation classification… techniques based on deep learning, …

… features are optimized by the classification error to make a … methods and deep learning
methods is also conducted in this article, which confirms the superiority of deep learning methods…