Likelihood-Ratio Approaches to Automatic Modulation Classification

By Jefferson L. Xu, Wei Su, Mengchu Zhou. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews), 2011

353 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Signal Processing

View Paper: https://www.semanticscholar.org/paper/2c4054eda4ca979dc94536e015fae1a285323e31

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Fan Meng
2. Xianbin Wang
3. Peng Chen
4. Lenan Wu
5. Arash Bahrammirzaee

In Signal Processing

1. Fan Meng
2. Xianbin Wang
3. Peng Chen
4. Lenan Wu

Citations in the corpus

• Automatic Modulation Classification: A Deep Learning Enabled Approach (2018, methodology): “The AMC methods based on maximum likelihood (ML) are also studied in [19], where the ML-AMCs have been proved to achieve the optimal performance in the scenarios with mathematical channel models.”