Discrimination of Earthquakes and Explosions Using Chirp-Z Transform Spectrum Features

التفاصيل البيبلوغرافية
العنوان: Discrimination of Earthquakes and Explosions Using Chirp-Z Transform Spectrum Features
المؤلفون: Lu Shi Jun, Bian Yin Ju, Li Rui, Huang Hanming
المصدر: CSIE (7)
بيانات النشر: IEEE, 2009.
سنة النشر: 2009
مصطلحات موضوعية: Computer science, business.industry, Bluestein's FFT algorithm, Speech recognition, Fast Fourier transform, Short-time Fourier transform, Spectral density, Pattern recognition, symbols.namesake, Fourier transform, Frequency domain, symbols, Chirp, Artificial intelligence, business, S transform
الوصف: To discriminate between earthquakes and explosions, spectrum range selection and spectrum resolution are sensitive and important constraint factors for recognition rate. This paper proposes a feature extracting algorithm for seismic wave spectrum analysis by using Chirp-Z transform. Initially by Fourier transform (FFT), overall spectrum layout is acquired. Upon this overall layout, seismic signals, suitable frequency range in the spectrum which contains most discriminative information are selected, then the proposed Chirp-Z transform is applied to get finer resolution spectrum, and at last more accurate spectrum features corresponding to different type signals are achieved. This algorithm is very useful to improve the accuracy of the discrimination problem and experiment results show its priority to classic Fourier transform.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::625cf50056916353c6c8ba5ad4893d29
https://doi.org/10.1109/csie.2009.696
رقم الأكسشن: edsair.doi...........625cf50056916353c6c8ba5ad4893d29
قاعدة البيانات: OpenAIRE