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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
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  <title>Power Spectral Density estimation (LTPDA Toolbox)</title>
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  <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Power Spectral Density estimation</h1>
  <hr>
  
  <p>
	<p>In this subsection we will focus on the evaluation of the PSD
(Power Spectral Density) for a given time-series signal. The
functionality is provided by a method of the <tt>ao</tt> class called
<p>
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        <tt>ao/psd</tt>
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which implements the Welch method of averaging modified periodograms (also referred to
as WOSA). More details can found in the dedicated <a href="sigproc_psd.html" >section</a> of the user manual.
</p>
<p>In this tutorial, we propose the following exercises based on the
estimation of the PSD of suitable time-series data:</p>
<p>
<ol>
  <li><a href="ltpda_training_topic_3_2_1.html" >Simply PSD</a>: a very basic starting exercise</li>
  <li><a href="ltpda_training_topic_3_2_2.html" >Windowing data</a>: introducing the usage of segment averaging/windwing/detrending</li>
  <li><a href="ltpda_training_topic_3_2_3.html" >Log-scale PSD on MDC1 data</a>: a "realistic" example from the first LTPDA Mock Data Challenge, employing the log-scale PSD estimation method</li>
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