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1 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2
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3 Generating non-white random noise means producing arbitrary long time series with a given spectral density.
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4 Such time series are needed for example for the following purposes:
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5 </p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 <ul>
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8 <li> To generate test data sets for programs that compute spectral densities, </li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 <li> as inputs for various simulations.</li>
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10 </ul>
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11 </p>
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12 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 One way of doing this is to apply digital filters (FIR or IIR) to white input noise.<br/>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 This approach is effectively implemented for the generation of <a href="ndim_ng.html"> multichannel noise </a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 with a given cross spectral density. <br/>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 Multichannel transfer functions are identified by an automatic fit procedure based
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 on a modified version of the vector-fitting algorithm
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 (see <a href="zdomainfit.html"> Z-Domain Fit </a> for further details on the algorithm). <br/>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 Partial fraction expansion of multichannel transfer functions and the implementation of
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20 <a href="sigproc_dfilt.html">filter</a> state initialization avoid the presence of unwanted 'warm-up period'.
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21 </p>
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22
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23 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 A different approach is implemented in LTPDA as <a href="franklin_ng.html">Franklin noise-generator</a>.<br/>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 It produces spectral densities according to a given pole zero model (see <a href="pzmodel.html">Pole/Zero Modeling</a>) and does not require any warm-up period. <br/>
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26 </p>
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