Empirical |
public class EmpiricalModeDecomposition
The EmpiricalModeDecomposition type exposes the following members.
Name | Description | |
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EmpiricalModeDecomposition | Initializes a new instance of the EmpiricalModeDecomposition class |
Name | Description | |
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AvgByDiffThreshold | Gets/sets the average by difference threshold. | |
MaximumAllowedAvgByDiff | Gets the maximum allowed average by difference value. | |
MaximumFractionAvgByDiffThresholdExceeded | Gets the maximum fraction of points for which the average by difference threshold can be exceeded. | |
MaximumNumberOfSiftingsForOneIMF | Gets the maximum number of siftings for one IMF component. | |
S | Maximum number of siftings, during which the number of extrema and the number of zero crossings remain constant, before the sifting process is stopped. |
Name | Description | |
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CreateInterpolationDataByContinuation | ||
CreateInterpolationDataByMirroring | ||
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
ExtractIntrinsicModeFunctionComponent | Extracts an intrinsic mode function component (IMF) from the signal (x, y). | |
ExtractIntrinsicModeFunctionComponents | Extracts the intrinsic mode function components (IMFCs) of a signal by empirical mode decomposition. | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
GetHashCode | Serves as the default hash function. (Inherited from Object) | |
GetType | Gets the Type of the current instance. (Inherited from Object) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
SubtractMeanEnvelope | Subtracts the mean envelope from the signal signal. | |
SubtractMeanEnvelope_1_1 | ||
ToString | Returns a string that represents the current object. (Inherited from Object) |
Reference:
[1] Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., … Liu, H. H. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454(1971), 903–995. https://doi.org/10.1098/rspa.1998.0193