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Clustering techniques are used to identify groups of watersheds which have similar flood characteristics. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory.
Conventionally, time series have been studied either in the time domain or the frequency 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.
Conventionally, time series have been studied either in the time domain or the frequency 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.
The Hilbert-Huang Transform (HHT) is a recently developed technique used to analyze nonstationary data. These results are compared to the results from the traditional methods such as those based on Fourier transform and other classical statistical tests.
The Hilbert-Huang Transform (HHT) is a recently developed technique used to analyze nonstationary data. These results are compared to the results from the traditional methods such as those based on Fourier transform and other classical statistical tests.
Clustering techniques are used to identify groups of watersheds which have similar flood characteristics. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory.
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