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Adaptive Denoising Method Based on Lifting Wavelet Neural Network of Fiber Optic Gyroscopes
Received date: 2012-12-20
Online published: 2025-05-26
The output of FOG involves stochastic noise which is difficult to be eliminated by traditional methods. An adaptive denoising method based on lifting wavelet neural network was proposed to improve the precision of fiber optic gyroscopes. The algorithm consists of transformation of lifting format, de-composition based on lifting wavelet, level-dependent threshold selecting and denoising based on wavelet neural network. The de-noising method based on wavelet and empirical mode decomposition were also been investigated to provide a comparison with the new method. Simulation experiment shows that the ALWNN method outperforms the other two methods.
DANG Shuwen . Adaptive Denoising Method Based on Lifting Wavelet Neural Network of Fiber Optic Gyroscopes[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2013 , 33(5) : 8 -10 . DOI: 10.15892/j.cnki.djzdxb.2013.05.007
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