Abstract
Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Zheng, Z.H., Shen, P., Yang, X.H., et al.: Wavelet Transform and the Application of MATLAB, pp. 1–156. Seismological Press, Beijing (2001)
Ran, Q.W., Tan, L.Y.: Wavelet Analysis and Fractional Fourier Transform and Its Application, pp. 1–244. Defense industry Press, Beijing (2002)
Grossmann, A., Morlet, J.G.: Decomposition of Hardy Function into Square Integrable Wavelets of Contant Shape. Siam J. Math. Anal. 15, 723–726 (1984)
Morlet, J.G., Arens, G., Fourgeau, E.: Wave Propagation and Sampling Theory: Complex Signal and Scattering in Multi-layered Media. Geophysics 47(1), 203–211 (1982)
Grossmann, A., Morlet, J.G.: Cycle-Octave and Related Transforms in Seismic Signals Analysis. Geoexploration 23, 85–102 (1985)
Meyer, Y.: Principle D’ Incertitude Bases Hilbertiennes et Algebra D’ Operataur. Bourbaki Seminaire, Asterisque (Societe Mathema-tique de France) 2, 662–690 (1985)
Daubechies, I.: Orthonormal Bases of Compactly Supported Wavelets. Communication on Pure and Applied Math. 41, 990–996 (1988)
Mallat, S.: Multiresolution Approximations and Wavelet Orthogonal Bases of L2(R). IEEE Trans. AMS 315, 68–87 (1989)
Yang, W.C., Shi, Z.Q., Hou, Z.Z., et al.: Discrete Wavelet Transform for Multiple Decomposition of Gravity Anomalies. Acta Geophysica Sinica 44(4), 534–541 (2001)
Meng, Z.B., Yang, L.H.: Wavelet Compression of Earthquake Data. Oil Geophysical Exploration 30(2), 70–75 (1995)
Liu, X.Q., Zhou, H.L., Zheng, Z.H., et al.: Identification Method of Weak Seismic Phases on the Basis of Wavelet Packet Transform. Acta Seismologica Sinica 20(4), 373–380 (1998)
Shen, P., Zheng, Z.Z., Liu, X.Q., et al.: Study on the Method for Comprehensive Discrimination of Small Earthquakes. Acta Seismologica Sinica 24(2), 169–175 (2002)
Du, X.X.: Wavelet-Based Analysis of Dynamic Seismicity Period. Earthquake 17(3), 257–264 (1997)
Zhang, Y.Z., Ding, P., Wang, J.Y., et al.: Relationship between Wavelet Analysis Results of Gravity and Earthquake in Hexi Region. Crustal Deformation and Earthquake 17(3), 26–32 (1997)
Yan, Z.G., Chen, J.H., Qian, J.D., et al.: Application of Method of Binary Wavelet Transformation in Resolution of Earthquake Precursor Signal Frequency. Earthquake 20(sup.), 76–81 (2000)
Shao, H.C., Du, X.X., Jin, X.S., et al.: The Application of the Wavelet Analysis in Earthquake Prediction. Earthquake Research in China 16(1), 48–52 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Wu, A., Hu, L., Li, L. (2012). The Analysis of Earthquake Precursory Based on Multiscale Technology of Wavelet Transform. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25781-0_43
Download citation
DOI: https://doi.org/10.1007/978-3-642-25781-0_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25780-3
Online ISBN: 978-3-642-25781-0
eBook Packages: EngineeringEngineering (R0)