Share
Nonstationarities in Hydrologic and Environmental Time Series (in English)
A. R. Rao
(Author)
·
K. H. Hamed
(Author)
·
Huey-Long Chen
(Author)
·
Springer
· Paperback
Nonstationarities in Hydrologic and Environmental Time Series (in English) - Rao, A. R. ; Hamed, K. H. ; Huey-Long Chen
$ 161.04
$ 169.99
You save: $ 8.95
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My WishlistsIt will be shipped from our warehouse between
Monday, June 10 and
Tuesday, June 11.
You will receive it anywhere in United States between 1 and 3 business days after shipment.
Synopsis "Nonstationarities in Hydrologic and Environmental Time Series (in English)"
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.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.