LTPDA Toolbox™ | contents | ![]() ![]() |
TDFIT fit a MATRIX of transfer function SMODELs to a matrix of input and output signals. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% DESCRIPTION: TDFIT fits a MATRIX of transfer function SMODELs to a set of input and output signals. It uses ao\tdfit as the core algorithm. CALL: b = tdfit(outputs, pl) INPUTS: outputs - an array of MATRIXs representing the outputs of a system, one per each experiment. pl - parameter list (see below) OUTPUTs: b - a pest object containing the best-fit parameters, goodness-of-fit reduced chi-squared, fit degree-of-freedom covariance matrix and uncertainties. Additional quantities, like the Information Matrix, are contained within the procinfo. The best-fit model can be evaluated from pest\eval. Parameters Description EXAMPLES: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Method Details | |
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Access | public |
Defining Class | matrix |
Sealed | 0 |
Static | 0 |
Sets for this method … |
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Default |
Default |
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no description | |||
Key | Default Value | Options | Description |
tdfit | |||
INPUTS | [] | none | A COLLECTION of MATRIXs, one per each experiment, containing the input A0s. |
MODELS | [] | none | A MATRIX of transfer function SMODELs. |
PADRATIO | 1 | none | PadRatio is defined as the ratio between the number of zero-pad points and the data length. Define how much to zero-pad data after the signal. Being tdfit a fft-based algorithm, no zero-padding might bias the estimation, therefore it is strongly suggested to do that. |
WHFLTS | [] | none | A MATRIX of FILTERBANKs containing the whitening filters per each output AO. |
PNAMES | {} [0x0] | none | A cell-array of parameter names to fit. |
P0 | [] | none | An array of starting guesses for the parameters. |
LB | [] | none | Lower bounds for the parameters. This improves convergency. Mandatory for Monte Carlo. |
UB | [] | none | Upper bounds for the parameters. This improves the convergency. Mandatory for Monte Carlo. |
ALGORITHM | 'fminsearch' |
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A string defining the fitting algorithm. fminunc, fmincon require 'Optimization Toolbox' to be installed. patternsearch, ga, simulannealbnd require 'Genetic Algorithm and Direct Search' to be installed. |
OPTSET | '' | none | An optimisation structure to pass to the fitting algorithm. See fminsearch, fminunc, fmincon, optimset, for details. See patternsearch, psoptimset, for details. See ga, gaoptimset, for details. See simulannealbnd, saoptimset, for details. |
SYMDIFF | 0 |
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Use symbolic derivatives or not. Only for gradient-based algorithm or for LinUnc option. |
DIFFORDER | 1 |
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Symbolic derivative order. Only for SymDiff option. |
FITUNC | 1 |
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Fit parameter uncertainties or not. |
UNCMTD | 'hessian' |
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Choose the uncertainties estimation method. For multi-channel fitting hessian is mandatory. |
LINUNC | 1 |
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Force linear symbolic uncertainties. |
GRADSEARCH | 0 |
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Do a preliminary gradient-based search using the BFGS Quasi-Newton method. |
MONTECARLO | 0 |
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Do a Monte Carlo search in the parameter space. Useful when dealing with high multiplicity of local minima. May be computer-expensive. Note that, if used, P0 will be ignored. It also requires to define LB and UB. |
NPOINTS | 100000 | none | Set the number of points in the parameter space to be extracted. |
NOPTIMS | 10 | none | Set the number of optimizations to be performed after the Monte Carlo. |
Example |
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plist('INPUTS', [[]], 'MODELS', [[]], 'PADRATIO', [1], 'WHFLTS', [[]], 'PNAMES', cell(0,0), 'P0', [[]], 'LB', [[]], 'UB', [[]], 'ALGORITHM', 'fminsearch', 'OPTSET', '', 'SYMDIFF', [false], 'DIFFORDER', [1], 'FITUNC', [true], 'UNCMTD', 'hessian', 'LINUNC', [true], 'GRADSEARCH', [false], 'MONTECARLO', [false], 'NPOINTS', [100000], 'NOPTIMS', [10]) |
Some information of the method matrix/tdfit are listed below: | |
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Class name | matrix |
Method name | tdfit |
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 | 0 |
Supported numeric types | {'double'} |
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Method: matrix/subsData | Method: matrix/tfe | ![]() |
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