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Autor(en): 
  • Huey-Long Chen
  • A. R. Rao
  • K. H. Hamed
  • Nonstationarities in Hydrologic and Environmental Time Series 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  September 2012  
    Genre:  Naturwissensch., Medizin, Technik 
     
    B / Cybernetics & systems theory / Earth and Environmental Science / geology / Hydrogeology / Mathematical Modeling and Industrial Mathematics / Mathematical modelling / Mathematical models / Maths for engineers / Probability & statistics / Probability and statistics / Statistics / Statistics, general / System Theory / Systems Theory, Control
    ISBN:  9789401039796 
    EAN-Code: 
    9789401039796 
    Verlag:  Springer Netherlands 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #45 - Water Science and Technology Library  
    Dimensionen:  H 235 mm / B 155 mm / D 22 mm 
    Gewicht:  598 gr 
    Seiten:  396 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e . the value of the signal at each instant in time is well defined . However, the time representation of a signal is poorly localized in frequency , i.e. little information about the frequency content of the signal at a certain frequency can be known by looking at the signal in the time domain . On the other hand, the representation of a signal in the frequency domain is well localized in frequency, but is poorly localized in time, and as a consequence it is impossible to tell when certain events occurred in time. In studying stationary or conditionally stationary processes with mixed spectra , the separate use of time domain and frequency domain analyses is sufficient to reveal the structure of the process . Results discussed in the previous chapters suggest that the time series analyzed in this book are conditionally stationary processes with mixed spectra. Additionally, there is some indication of nonstationarity, especially in longer time series.
      



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