Skip to content
/ MCCFN Public

Code for "A Multi-scale Complex-valued Convolutional Fusion Network for Automatic Modulation Recognition"

Notifications You must be signed in to change notification settings

Miraitwo/MCCFN

Repository files navigation

MCCFN

The article is currently under submission.

Preparation

Data

Experiments were conducted on four datasets: RMLradio2016.10a, RMLradio2016.10b and RML22.

The dataset can be downloaded from the DeepSig official website.

Environment Setup

  • pytorch = 2.4.0
  • cuda = 11.8
  • python = 3.8

Comparison with other models on the 2016a dataset.

Compare model:MCDformer,AWN,AvgNet,PETCGDNNand CLDNN

Some of the code is borrowed from MCDformer,AWN,CDSCNN and we thank them for their excellent work.

About

Code for "A Multi-scale Complex-valued Convolutional Fusion Network for Automatic Modulation Recognition"

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages