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IEEE Communications Letters, ISSN 1089-7798, 03/2016, Volume 20, Issue 3, pp. 450 - 453
In this letter, we propose a hybrid maximum likelihood (HML) classifier for continuous phase modulation (CPM). To the best of our knowledge, the proposed... 
Maximum likelihood estimation | CPM | Phase modulation | Automatic modulation classification | Markov processes | Silicon | ML estimation | Computational complexity | EM algorithm | Principal component analysis | TELECOMMUNICATIONS | principal component analysis
Journal Article
Digital Signal Processing, ISSN 1051-2004, 12/2017, Volume 71, pp. 108 - 116
Modulation identification of the transmitted signals remain a challenging area in modern intelligent communication systems like cognitive radios. The... 
Deep neural networks | I-Q diagrams | Pattern recognition | Automatic modulation classification | Digital modulation signals | RECOGNITION | ENGINEERING, ELECTRICAL & ELECTRONIC | Data mining | Neural networks | Analysis | Machine learning | Fading channels | Algorithms
Journal Article
IEEE Transactions on Wireless Communications, ISSN 1536-1276, 08/2012, Volume 11, Issue 8, pp. 2742 - 2750
Journal Article
IEEE Transactions on Vehicular Technology, ISSN 0018-9545, 09/2018, Volume 67, Issue 9, pp. 8192 - 8204
Journal Article
IEEE Transactions on Wireless Communications, ISSN 1536-1276, 01/2017, Volume 16, Issue 1, pp. 400 - 411
Journal Article
IEEE Transactions on Vehicular Technology, ISSN 0018-9545, 11/2018, Volume 67, Issue 11, pp. 10760 - 10772
Journal Article
IEEE Communications Letters, ISSN 1089-7798, 10/2013, Volume 17, Issue 10, pp. 1881 - 1884
A novel algorithm is proposed for automatic modulation classification in multiple-input multiple-output spatial multiplexing systems, which employs... 
Blind equalizers | Channel estimation | Modulation | Automatic modulation classification | multiple-input multiple-output | Vectors | MIMO | Signal to noise ratio | fourth-order cumulant | TELECOMMUNICATIONS
Journal Article
IEEE Transactions on Communications, ISSN 0090-6778, 08/2010, Volume 58, Issue 8, pp. 2324 - 2332
Journal Article
IEEE Communications Letters, ISSN 1089-7798, 05/2018, Volume 22, Issue 5, pp. 938 - 941
Motivated by the fact that moments of the received signal are easy to compute and can provide a simple way to automatically classify the modulation of the... 
Support vector machines | Machine learning algorithms | genetic programming | Modulation | Automatic modulation classification | Receivers | moments-based classification | Probability density function | Feature extraction | machine learning | Signal to noise ratio | support vector machines | TELECOMMUNICATIONS
Journal Article
IEEE Communications Letters, ISSN 1089-7798, 1/2020, pp. 1 - 1
This paper proposes a cost-efficient convolutional neural network (CNN) for robust automatic modulation classification (AMC) deployed for cognitive radio... 
deep learning | skip connection | Automatic modulation classification | convolutional neural network
Journal Article
IEEE Communications Letters, ISSN 1089-7798, 1/2020, pp. 1 - 1
In this paper, we propose an improved convolutional neural network (CNN)-based automatic modulation classification network (IC-AMCNet), an algorithm to... 
convolutional neural network (CNN) | beyond fifth generation (B5G) | Automatic modulation classification
Journal Article
IEEE Communications Letters, ISSN 1089-7798, 10/2017, Volume 21, Issue 10, pp. 2162 - 2165
How to reduce complexity of the practical automatic modulation classification systems is a very active research area. Moreover, keeping the classification... 
Training | Neural networks | Modulation | Automatic modulation classification | Feature extraction | Complexity theory | Image reconstruction | deep neural network | Sorting | k -sparse autoencoders">k -sparse autoencoders
Journal Article
IEEE Photonics Technology Letters, ISSN 1041-1135, 07/2019, Volume 31, Issue 13, pp. 1092 - 1095
With the rapid development of intelligent communication systems, classical problems, such as automatic modulation classification (AMC), have gained extensive... 
Training | neural networks (NN) | millimeter wave over fiber (MMWoF) | Automatic modulation classification (AMC) | Feature extraction | Adaptive optics | Optical modulation | Optical noise | Signal to noise ratio | SIGNAL | FORMAT IDENTIFICATION | PHYSICS, APPLIED | OPTICS | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, 12/2019, Volume 2019, Issue 1, pp. 1 - 15
Journal Article
IEEE Transactions on Wireless Communications, ISSN 1536-1276, 08/2008, Volume 7, Issue 8, pp. 3098 - 3105
Journal Article
by Afan, A and Fan, YY
IEEE COMMUNICATIONS LETTERS, ISSN 1089-7798, 10/2017, Volume 21, Issue 10, pp. 2162 - 2165
How to reduce complexity of the practical automatic modulation classification systems is a very active research area. Moreover, keeping the classification... 
Automatic modulation classification | TELECOMMUNICATIONS | deep neural network | k-sparse autoencoders
Journal Article
Expert Systems With Applications, ISSN 0957-4174, 01/2015, Volume 42, Issue 1, pp. 1 - 8
Journal Article
IEEE Access, ISSN 2169-3536, 2019, Volume 7, pp. 94604 - 94613
In non-cooperative communication scenarios, automatic modulation classification (AMC) is the premise of information acquisition. It has been a difficult issue... 
Deep learning | receptive field | Convolution | Modulation | Automatic modulation classification | Interference | deep hierarchical network | Feature extraction | Natural language processing | Signal to noise ratio | signal-to-noise ratio weight | COMPUTER SCIENCE, INFORMATION SYSTEMS | TELECOMMUNICATIONS | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
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