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
Link To Document :
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