LTPDA Toolbox™ |
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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:

- IFO signals
- Inputs for the experiments
- Whitening filters
- Fit model

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 |
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no description |
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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