LTPDA Toolbox | contents | ![]() ![]() |
The following sections gives an introduction to the generation of model noise using the noise generator implemented in LTPDA.
See Generating model noise for more general information on this.
Franklin's method does not require any 'warm up' period. It starts with a transfer function given as ratio of two polynomials.
The generator operates on a real state vector y of length n which is
maintained between invocations. It produces samples of the time series in equidistant steps T = 1/fs, where fs is the sampling frequency.
ltpda_noisegen uses pzm2ab.m and franklin.m to generate a time-series from a given pzmodel
>> [b, pl1, pl2] = ltpda_noisegen(pl) >> [b, pl1] = ltpda_noisegen(pl) >> b = ltpda_noisegen(pl1, pl2)
Depending on the Inputs different functions are called by ltpda_noisegen.
First a parameter list of the input parameters is to be done. For further information on this look at Creating parameter lists from parameters.
The most common case would be to start from a pole zero model pzm, the number of seconds the resulting time series should have nsecs and the sampling frequency fs. In this case all of the four main functions mentioned above are called one after the other.
The function call can then look like this:
>> [b, pl1, pl2] = ltpda_noisegen(pl)
The matrices Tinit, Tprop and E can be known from a previous calculation (i.e ltpda_noisegen, LISO).
These matrices can be stored as parameters of a parameter list and inputted into ltpda_noisegen.
In this case the function starts the operation with calling nginit first and finally ngprop.
The output will be the same as for case 1.
In this case a state vector y known from a previous run of the function is given as input together with the matrices.
ltpda_noisegen will now only call ngprop.
The output will again be the same as above.
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Generating model noise | Pole/Zero Modelling | ![]() |
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