Nonstationarities in Hydrologic and Environmental Time Series:
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 loca...
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| Hauptverfasser: | , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Dordrecht
Springer Netherlands
2003
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| Schriftenreihe: | Water Science and Technology Library
45 |
| Schlagworte: | |
| Online-Zugang: | BTU01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XXVII, 365 p) |
| ISBN: | 9789401001175 |
| DOI: | 10.1007/978-94-010-0117-5 |
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| 520 | |a 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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| spelling | Ramachandra Rao, A. Verfasser aut Nonstationarities in Hydrologic and Environmental Time Series by A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen Dordrecht Springer Netherlands 2003 1 Online-Ressource (XXVII, 365 p) txt rdacontent c rdamedia cr rdacarrier Water Science and Technology Library 45 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 Earth Sciences Hydrogeology Systems Theory, Control Mathematical Modeling and Industrial Mathematics Statistics, general Earth sciences System theory Mathematical models Statistics Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Hydrologie (DE-588)4026309-5 gnd rswk-swf Hydrologie (DE-588)4026309-5 s Zeitreihenanalyse (DE-588)4067486-1 s 1\p DE-604 Hamed, Khaled H. aut Chen, Huey-Long aut Erscheint auch als Druck-Ausgabe 9789401039796 https://doi.org/10.1007/978-94-010-0117-5 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Ramachandra Rao, A. Hamed, Khaled H. Chen, Huey-Long Nonstationarities in Hydrologic and Environmental Time Series Earth Sciences Hydrogeology Systems Theory, Control Mathematical Modeling and Industrial Mathematics Statistics, general Earth sciences System theory Mathematical models Statistics Zeitreihenanalyse (DE-588)4067486-1 gnd Hydrologie (DE-588)4026309-5 gnd |
| subject_GND | (DE-588)4067486-1 (DE-588)4026309-5 |
| title | Nonstationarities in Hydrologic and Environmental Time Series |
| title_auth | Nonstationarities in Hydrologic and Environmental Time Series |
| title_exact_search | Nonstationarities in Hydrologic and Environmental Time Series |
| title_full | Nonstationarities in Hydrologic and Environmental Time Series by A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen |
| title_fullStr | Nonstationarities in Hydrologic and Environmental Time Series by A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen |
| title_full_unstemmed | Nonstationarities in Hydrologic and Environmental Time Series by A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen |
| title_short | Nonstationarities in Hydrologic and Environmental Time Series |
| title_sort | nonstationarities in hydrologic and environmental time series |
| topic | Earth Sciences Hydrogeology Systems Theory, Control Mathematical Modeling and Industrial Mathematics Statistics, general Earth sciences System theory Mathematical models Statistics Zeitreihenanalyse (DE-588)4067486-1 gnd Hydrologie (DE-588)4026309-5 gnd |
| topic_facet | Earth Sciences Hydrogeology Systems Theory, Control Mathematical Modeling and Industrial Mathematics Statistics, general Earth sciences System theory Mathematical models Statistics Zeitreihenanalyse Hydrologie |
| url | https://doi.org/10.1007/978-94-010-0117-5 |
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