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1 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 Training session 3 is a tutorial of how to estimate spectral
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3 properties of the signals, employing the instruments provided by the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 LTPDA Toolbox. As described in the devoted User Manual <a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 href="sigproc_spec.html"> section</a>, spectral estimation is a
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6 branch of the signal processing, performed on data and based on
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7 frequency-domain techniques.
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8 </p>
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9 <p>The focus of the tools is on
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10 time-series objects, whose spectral content needs to be estimated.
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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 We will learn here how to use the tools to evaluate univariate and
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14 multivariate analyses. </p>
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15 <p> The topic is divided as follows:
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16
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17 <ul>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 <li><a href="ltpda_training_topic_3_2.html">Exercises on Power
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19 Spectral Density estimation</a> </li>
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20 <li><a href="ltpda_training_topic_3_5.html">Exercises on Transfer Functions estimation</a> </li>
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21 <li><a href="ltpda_training_topic_3_6.html">IFO/Temperature Example - Spectral Analysis</a> </li>
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22 </ul>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23
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24 </p> |