EigenSpectrum (FPScript)
Computes the EigenAnalysis Spectral estimators spectrum.
Syntax
EigenSpectrum(Signal, [ SpectrumType = SPECTRUM_EIGEN_DB ], [ Algorithm = ALGORITHM_EIGEN_MUSIC ], [ Order ], [ SignalSpace ], [ FrequencyCount ], [ StartingFrequency = 0 ] [ , EndingFrequency = 0.5 ])
The syntax of the EigenSpectrum function consists of the following parts:
Part |
Description |
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Signal |
The data to be analyzed. The data must have a constant sampling rate and must not contain void values. Permitted data structures are data series, data matrix, signal und signal series. All numeric data types are permitted. Void values are not permitted in this argument. For the X component additional restrictions do apply.The values must have a constant positive spacing. Void values are not permitted in this argument. If the argument is a list, then the function is executed for each element of the list and the result is also a list. |
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SpectrumType |
The fixed or adjustable data window to be applied to the data. The argument SpectrumType can have the following values:
If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value SPECTRUM_EIGEN_DB. |
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Algorithm |
The EigenAnalysis algorithm to be used. The argument Algorithm can have the following values:
If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value ALGORITHM_EIGEN_MUSIC. |
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Order |
The FB data matrix model order. The valid range is 2 to the smaller of 200 and 2/3 the data length. The default is the smaller of 50 and 2/3 the data length. Permitted data structures are scalar value. All integral data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. |
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SignalSpace |
The number of principal components in the SVD algorithm. The valid range is between 1 and the Eigenanalysis model order. The default is the smaller of 6 and the model order. Permitted data structures are scalar value. All integral data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. |
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FrequencyCount |
The number of frequencies to be computed in the spectrum. The valid range is between 257 and 65537 for a spectrum with a fixed length. The value 0 calculates an adaptive spectrum. The default is 8193 in case of a signal series or data matrix and adaptive otherwise. Permitted data structures are scalar value. All integral data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. |
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StartingFrequency |
The normalized starting frequency for the spectrum. Permitted data structures are scalar value. All real data types are permitted. The value must be greater or equal to 0 and less or equal to 0.5. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value 0. |
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EndingFrequency |
The normalized ending frequency for the spectrum. Permitted data structures are scalar value. All real data types are permitted. The value must be greater or equal to 0 and less or equal to 0.5. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value 0.5. |
Remarks
The data structure of the result is a signal or signal series. If the argument Signal is a data series or data matrix, then the X component of the result contains Nyquist-normalized frequencies.
Available in
Option Spectral Analysis
Examples
EigenSpectrum(Signal, SPECTRUM_EIGEN_DB, ALGORITHM_EIGEN_MUSIC, 40, 6, 0, 0, 0)
Calculates the Eigenanalysis spectrum of the 'Signal' signal. This procedure is particularly important for frequency estimation when data records are very short. The dB spectrum type, the MUSIC algorithm and the order of 40 are selected. The signal subspace is set to 6 and the increment is set to adaptive. This is an example from the Spectral Estimators Tutorial.