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  • 1
    Digitale Medien
    Digitale Medien
    Springer
    International journal of earth sciences 85 (1996), S. 110-115 
    ISSN: 1437-3262
    Schlagwort(e): Counting statistics ; Earthquake ; 1/f noise
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Geologie und Paläontologie
    Notizen: Abstract In a variety of biological and physical phenomena, temporal fluctuations are found, which are not explainable as consequences of statistically independent random events. If these fluctuations are characterized by a power spectrum density S(f) decaying as f −β at low frequencies, this behaviour is called 1/f noise. Counting statistics applied to earthquake activity data leads to three time scales with different characteristics, represented by the exponent β: at interval lengths less than 1 h, the shocks are randomly distributed as in a Poisson process. For medium time intervals (1 day to 3 months), the exponent 1 + β is larger (1.4 for M 0=3), but approaches unity for higher threshold magnitudes M 0. In longer time ranges the exponent assumes values near 1.55, however, with increasing statistical variation at higher M 0, due to lower counts. The temporal sequence is different from white noise; thus, it might be fruitful to apply neural network algorithms, because this method allows predictions in some other cases with similar characteristics.
    Materialart: Digitale Medien
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Digitale Medien
    Digitale Medien
    Springer
    Geologische Rundschau 85 (1996), S. 110-115 
    ISSN: 0016-7835
    Schlagwort(e): Key words Counting statistics ; Earthquake ; 1/f noise
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Geologie und Paläontologie
    Notizen: Abstract  In a variety of biological and physical phenomena, temporal fluctuations are found, which are not explainable as consequences of statistically independent random events. If these fluctuations are characterized by a power spectrum density S ( f ) decaying as f –β at low frequencies, this behaviour is called 1/ f noise. Counting statistics applied to earthquake activity data leads to three time scales with different characteristics, represented by the exponent β: at interval lengths less than 1 h, the shocks are randomly distributed as in a Poisson process. For medium time intervals (1 day to 3 months), the exponent 1+β is larger (1.4 for M 0=3), but approaches unity for higher threshold magnitudes M 0. In longer time ranges the exponent assumes values near 1.55, however, with increasing statistical variation at higher M 0, due to lower counts. The temporal sequence is different from white noise; thus, it might be fruitful to apply neural network algorithms, because this method allows predictions in some other cases with similar characteristics.
    Materialart: Digitale Medien
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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