JOURNAL ARTICLE

Debris Flow Infrasound Denoising Based on Improved Wavelet Threshold Algorithm

Xuelei DuXiaopeng LengS. Nageswara RaoLiangyu Feng

Year: 2022 Journal:   2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI) Pages: 810-816

Abstract

Aiming at the problem of signal distortion caused by improper threshold in the processing of debris flow infrasound signals by the traditional wavelet threshold algorithm, an improved adaptive threshold algorithm is proposed. Meanwhile, the improved threshold function is constructed to integrate the advantages of soft and hard threshold functions, and its feasibility is proved on the principle of wavelet threshold denoising. Simulation experiments are carried out on MATLAB software: the improved signal denoising method can get higher SNR and lower mean square error than the traditional method. The improved method is applied to the measured debris flow infrasound signal, and it is found that the improved method can effectively remove the noise and retain the effective signal, which proves that it has certain feasibility in the application of debris flow infrasound signal denoising.

Keywords:
Noise reduction Wavelet SIGNAL (programming language) Distortion (music) Infrasound Algorithm Noise (video) Computer science Debris flow Reduction (mathematics) Artificial intelligence Mathematics Acoustics Debris Telecommunications Meteorology Physics

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Citation History

Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Seismic Waves and Analysis
Physical Sciences →  Earth and Planetary Sciences →  Geophysics
Ultrasonics and Acoustic Wave Propagation
Physical Sciences →  Engineering →  Mechanics of Materials
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