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Springer Hilbert-Huang Transform Analysis of Time Series Book

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Description

Explore advanced signal processing techniques with this Springer publication from the Water Science and Technology Library. This volume focuses on the Hilbert-Huang Transform (HHT) and Empirical Mode Decomposition (EMD) to address the non-linearity and non-stationarity found in many natural time series. By utilizing the local characteristic time scale of data, the HHT method offers a precise time-frequency representation compared to conventional signal processing methods. This approach provides a physically meaningful interpretation of underlying dynamic processes. Additionally, the EMD functions as a filter to extract signal variability across different scales, making it an efficient tool for hydrological and environmental data analysis.

Key Features

This Springer book provides an adaptive method for analyzing non-linear and non-stationary natural time series.

The Hilbert-Huang Transform (HHT) uses local characteristic time scales to offer precise time-frequency representations.

Readers can gain a physically meaningful interpretation of underlying dynamic processes through HHT methods.

Empirical Mode Decomposition (EMD) acts as a filter to extract signal variability across various scales.

Part of the Water Science and Technology Library (Volume 60) for specialized hydrological research.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
30 November 2010
Listed Since
20 September 2010

Barcode

No barcode data available

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