Simulation design of signal noise reduction algorithm based on neural network
Conference: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
12/17/2021 - 12/19/2021 at Shenyang, China
Proceedings: ICMLCA 2021
Pages: 6Language: englishTyp: PDF
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Authors:
Zhou, Linhao; Yang, Jin; Xu, Jiulong (Equipment Engineering College, Shenyang Ligong University, Shenyang, China)
Hao, Yongping (Mechanical Engineering College, Shenyang Ligong University, Shenyang, China)
Abstract:
In order to de-noise the noise signal generated by radar and other military equipment and recover the original signal, two simulation models, Bp neural network and Elman neural network, were established by using MATLAB simulation software to de-noise the signal. Some parameters of neural network in signal denoising process are changed to observe the influence of these parameters on neural network. Through the final simulation analysis, it is found that Elman neural network has better effect than Bp neural network, which is more suitable for noise processing and data prediction of radar and other military equipment, while Bp neural network is more suitable for solving problems with complex internal mechanism.