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1.

The empirical mode decomposition (EMD) is a necessary step to reduce any given data into a collection of intrinsic mode functions (IMF) to which the Hilbert spectral analysis can be applied. An IMF is defined as a function that satisfies the following requirements:

1. In the whole data set, the number of extrema and the number of zero-crossings must either be equal or differ at most by one.

2. At any point, the mean value of the envelope defined by the local maxima and the envelope defined by the local minima is zero.

Answered by Jack Johnson, 14 Sep '09 09:37 pm
1. In the whole data set, the number of extrema and the number of zero-crossings must either be equal or differ at most by one.

2. At any point, the mean value of the envelope defined by the local maxima and the envelope defined by the local minima is zero.

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The Empirical Mode Decomposition is a technique to decompose a given signal into a set of elemental signals called Intrinsic Mode Functions. The Empirical Mode Decomposition is the base of the so-called Hilbert-Huang Transform that comprises also a Hilbert Spectral Analysis and an instantaneous frequency computation. A modified improved algorithm for the Empirical Mode Decomposition is implemented. The output is a set of AM/FM modulated signal.

To use it, it is enough to input the signal, two resolutions in dB (~50) and a step value

Answered by Shikha Aggarwal, 15 Sep '09 12:47 am
To use it, it is enough to input the signal, two resolutions in dB (~50) and a step value

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