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  <title>Generating model noise (LTPDA Toolbox)</title>
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  <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Generating model noise</h1>
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  <p>
	<p>

Generating non-white random noise means producing arbitrary long time series with a given spectral density.
Such time series are needed for example for the following purposes:
</p>
<p>
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		<li> To generate test data sets for programs that compute spectral densities, </li>
		<li> as inputs for various simulations.</li>
	</ul>
</p>
<p>
  One way of doing this is to apply digital filters (FIR or IIR) to white input noise.<br/>
  This approach is effectively implemented for the generation of <a href="ndim_ng.html"> multichannel noise </a>
  with a given cross spectral density. <br/>
  Multichannel transfer functions are identified by an automatic fit procedure based
  on a modified version of the vector-fitting algorithm
  (see <a href="zdomainfit.html"> Z-Domain Fit </a> for further details on the algorithm). <br/>
  Partial fraction expansion of multichannel transfer functions and the implementation of
  <a href="sigproc_dfilt.html">filter</a> state initialization avoid the presence of unwanted 'warm-up period'.
</p>

<p>
	A different approach is implemented in LTPDA as <a href="franklin_ng.html">Franklin noise-generator</a>.<br/>
	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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author	Daniele Nicolodi <nicolodi@science.unitn.it>
date	Tue, 06 Dec 2011 11:09:25 +0100
parents	f0afece42f48
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