LTPDA Toolbox™ | contents | ![]() ![]() |
NOISEGEN1D generates colored noise from white noise. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% DESCRIPTION: noisegen1D can work in two different modes: ------------------------------------------------------------------------ 1) Generates colored noise from white noise with a given spectrum. The function constructs a coloring filter through a fitting procedure to the model provided. If no model is provided an error is prompted. The colored noise provided has one-sided psd corresponding to the input model. This mode correspond to the 'Default' set for the method (see the list of parameters). ALGORITHM: 1) Fit a set of partial fraction z-domain filters using utils.math.psd2tf 2) Convert to array of MIIR filters 3) Filter time-series in parallel CALL: b = noisegen1D(a, pl) INPUT: - a is a white noise time-series analysis object or a vector of analysis objects - pl is a plist with the input parameters OUTPUT: - b Colored time-series AOs. The coloring filters used are stored in the objects procinfo field under the parameter 'Filt'. ------------------------------------------------------------------------ 2) Generates noise coloring filters for given input psd models. This mode correspond to the 'Filter' set for the method (see the list of parameters). ALGORITHM: 1) Fit a set of partial fraction z-domain filters 2) Convert to array of MIIR filters CALL: fil = noisegen1D(psd, pl) INPUT: - psd is a fsdata analysis object representing the desired model for the power spectral density of the colored noise - pl is a plist with the input parameters OUTPUT: - fil is a filterbank parallel object which elements are miir filters. Filters are initialized to avoid startup transients. ------------------------------------------------------------------------ Parameters Description %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Method Details | |
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Access | public |
Defining Class | ao |
Sealed | 0 |
Static | 0 |
Sets for this method … |
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Default |
Filter |
Default |
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no description | |||
Key | Default Value | Options | Description |
noisegen1D | |||
YUNITS | '' | none | Unit on Y axis. If left empty, it will take the y-units from the input object |
MODEL | [] | none | A frequency-series AO describing the model psd |
MAXITER | 30 | none | Maximum number of iterations in fit routine. |
POLETYPE | 3 |
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Choose the pole type for fitting:
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MINORDER | 2 | none | Minimum order to fit with. |
MAXORDER | 25 | none | Maximum order to fit with. |
WEIGHTS | 3 | none | Choose weighting for the fit:
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PLOT | 0 |
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Plot results of each fitting step. |
DISP | 0 |
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Display the progress of the fitting iteration. |
MSEVARTOL | 0.01 | none | Mean Squared Error Variation - Check if the realtive variation of the mean squared error is smaller than the value specified. This option is useful for finding the minimum of Chi-squared. |
FITTOL | 0.01 | none | Mean Squared Error Value - Check if the mean squared error value is lower than the value specified. |
RAND_STREAM | [] | none | Internal MATLAB state of the pseudorandom number generator. You can set the state with a structure which should contain all properties of the MATLAB class RandStream |
Example |
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plist('YUNITS', '', 'MODEL', [[]], 'MAXITER', [30], 'POLETYPE', [3], 'MINORDER', [2], 'MAXORDER', [25], 'WEIGHTS', [3], 'PLOT', [false], 'DISP', [false], 'MSEVARTOL', [0.01], 'FITTOL', [0.01], 'RAND_STREAM', [[]]) |
Filter |
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no description | |||
Key | Default Value | Options | Description |
noisegen1D | |||
FS | 1 | none | The sampling frequency to design for. |
IUNITS | '' | none | The input units of the filter. |
OUNITS | '' | none | The output units of the filter. |
MAXITER | 30 | none | Maximum number of iterations in fit routine. |
POLETYPE | 3 |
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Choose the pole type for fitting:
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MINORDER | 2 | none | Minimum order to fit with. |
MAXORDER | 25 | none | Maximum order to fit with. |
WEIGHTS | 3 | none | Choose weighting for the fit:
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PLOT | 0 |
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Plot results of each fitting step. |
DISP | 0 |
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Display the progress of the fitting iteration. |
MSEVARTOL | 0.01 | none | Mean Squared Error Variation - Check if the realtive variation of the mean squared error is smaller than the value specified. This option is useful for finding the minimum of Chi-squared. |
FITTOL | 0.01 | none | Mean Squared Error Value - Check if the mean squared error value is lower than the value specified. |
RAND_STREAM | [] | none | Internal MATLAB state of the pseudorandom number generator. You can set the state with a structure which should contain all properties of the MATLAB class RandStream |
Example |
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plist('FS', [1], 'IUNITS', '', 'OUNITS', '', 'MAXITER', [30], 'POLETYPE', [3], 'MINORDER', [2], 'MAXORDER', [25], 'WEIGHTS', [3], 'PLOT', [false], 'DISP', [false], 'MSEVARTOL', [0.01], 'FITTOL', [0.01], 'RAND_STREAM', [[]]) |
Some information of the method ao/noisegen1D are listed below: | |
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Class name | ao |
Method name | noisegen1D |
Category | Signal Processing |
Package name | ltpda |
VCS Version | 967b0eec0dece803a81af8ef54ad2f8c784b20b2 |
Min input args | 1 |
Max input args | -1 |
Min output args | 1 |
Max output args | -1 |
Can be used as modifier | 1 |
Supported numeric types | {'double'} |
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Method: ao/mve | Method: ao/noisegen2D | ![]() |
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