Automatic Modulation Recognition Based on Hybrid Neural Network

Algorithm 1

Algorithm description of the MCBL model.

Input: Modulation signal dataset

Output: MCBL model, Recognition rate, Confusion matrix

1: Part 1: Data preprocessing

2: fordo

3: 

4: end for

5:

6: Part 2: Model training

7: (Initialization);

8: while decrease within 30 epochs do

9: fordo

10:  

  // and are the weights and bias of CSFE module, and is the ReLU activation function

11:  

  // and are the weights and bias of BTFE module

12:  

13:  

  // is an element in set , and is a vector

14:  

15:  

  // is the global attention factors

16:  

17:  end for

18:  fordo

19:   

20:  end for

21: end while

22: Part 3: Model testing

23: Input testing data into the model

24:

25: return