Abstract: In view of the problem that the recognition method of digital signal modulation mode was easy to be affected by noise and the recognition error was large, we designed a recognition method of digital signal modulation mode based on wavelet neural network. Firstly, we collected digital signal and extracted the modulation recognition feature from the signal as the classification basis of the digital signal modulation mode. Secondly, we established classifier of digital signals modulation recognition based on neural network, and selected particle swarm optimization algorithm to determine the parameters of the neural network, so as to realize the digital signal modulation recognition. Finally, the simulation test of digital signals modulation recognition was realized on MATLAB[KG*6]2016 platform. The test results show that, even if the signaltonoise ratio of digital signal is low, the wavelet neural network can still obtain the ideal digital signal modulation recognition results, and the digital signal modulation recognition rate is higher than that of the contrast method, thus improving the performance of digital signal modulation recognition.

Key words: classifier design, neural network, digital signal, particle swarm optimization (PSO) algorithm, modulation mode, recognition method