| LTPDA Toolbox™ | contents | ![]() |
At this point we have all the data we need to perform a linear fir to the IFO output data. We start by loading the data we need that we have produced in the previous sections. In particulr:
odat = matrix('output.mat');
idat = matrix('input.mat');
wf = matrix('whitening_filter.mat');
H = ssm('fitting_model.mat');
Then we define input ports, output ports and parameters names.
% define input port-names for the different experiments
InputNames = {{'GUIDANCE.ifo_x1'}, {'GUIDANCE.ifo_x12'}};
% define output port-names for the different experiments
OutputNames = {{'DELAY_IFO.x1', 'DELAY_IFO.x12'}, {'DELAY_IFO.x1','DELAY_IFO.x12'}};
% parameters names
params = {'FEEPS_XX', 'CAPACT_TM2_XX', 'IFO_X12X1', 'EOM_TM1_STIFF_XX', 'EOM_TM2_STIFF_XX'};
% Input signals
is1ao = idat(1).getObjectAtIndex(1); % extract the AOs
is2ao = idat(2).getObjectAtIndex(2);
iS = collection(is1ao, is2ao); % put inputs inside a collection
% set numerical derivative step as 1% of the nominal values
diffStep = [1, 1, 1e-4, 1.935e-06, 2.0e-6] .* 0.01;
We have all the data we need for starting the fit. We start defining a 'plist' with all the parameters we need for the current fit session.
plfit = plist(...
'FitParams', params ,...
'diffStep', diffStep, ...
'Model', H, ...
'Input', iS, ...
'INNAMES', InputNames, ...
'OUTNAMES', OutputNames, ...
'WhiteningFilter', wf, ...
'tol', 1, ...
'Nloops', 10, ...
'Ncut', 1e3);
fpars = linfitsvd(odat, plfit);
If you want more information about 'linfitsvd' you have to type in MATLAB command line:
help matrix/linfisvd
Default |
|||
|---|---|---|---|
| no description | |||
| Key | Default Value | Options | Description |
| MODEL | [] | none | System model. It have to be parametric. A matrix of smodel objects or a ssm object |
| INNAMES | {} [0x0] | none | A cell array containing cell arrays of the input ports names for each experiment. Used only with ssm models. |
| OUTNAMES | {} [0x0] | none | A cell array containing cell arrays of the output ports names for each experiment. Used only with ssm models. |
| FITPARAMS | {} [0x0] | none | A cell array with the names of the fit parameters |
| INPUT | [] | none | Collection of input signals |
| WHITENINGFILTER | [] | none | The multichannel whitening filter. A matrix object of filters |
| NLOOPS | 1 | none | Number of desired iteration loops. |
| NCUT | 100 | none | Number of bins to be discharged in order to cut whitening filter transients |
| TOL | 1 | none | Convergence threshold for fit parameters |
| DIFFSTEP | [] | none | Numerical differentiation step for ssm models |
We are now ready to save our fit results.
fpars.save('fit_linear.mat');
|
Building whitening filters | Results and Comparison | ![]() |
©LTP Team