DocumentCode
1854031
Title
Using AR Model and BP Neural Network to Identify Microseism Signal
Author
Chang-peng, Ji ; Li-li, Liu
Author_Institution
Sch. of Electron. & Inf. Eng., Liaoning Tech. Univ., Huludao, China
fYear
2010
fDate
22-24 Jan. 2010
Firstpage
134
Lastpage
138
Abstract
According to the characteristics of broad frequency and abundant spectral components of mine microseismic signal, we use AR model parameters and BP neural network to propose a method of filtering treatment for the signal and noise with different frequency ranges. We can use this method to separate noise and signal, and decompose different frequency band signals, so we can achieve the goal of filtering. The experimental results suggest that we can effectively remove the noise of microseismic abnormal signal by using AR model parameters and BP neural network, and this method can be used in the microseismic prediction and the pretreatment of microseismic signal.
Keywords
autoregressive processes; backpropagation; filtering theory; geophysical signal processing; neural nets; seismic waves; seismology; signal denoising; AR model; BP neural network; filtering treatment method; frequency band signals; microseism signal identification; microseismic abnormal signal; Fluctuations; Frequency; Geology; Information filtering; Information filters; Interference; Neural networks; Predictive models; Signal analysis; Signal processing; AR model; BP neural network; identify; microseism signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Future Networks, 2010. ICFN '10. Second International Conference on
Conference_Location
Sanya, Hainan
Print_ISBN
978-0-7695-3940-9
Electronic_ISBN
978-1-4244-5667-3
Type
conf
DOI
10.1109/ICFN.2010.26
Filename
5431866
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