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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 Spectral estimation is a branch of the signal processing, performed on data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 and based on frequency-domain techniques.<br>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 Within the LTPDA toolbox many functions of the Matlab <a href="matlab:doc('signal')" >Signal Processing Toolbox</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 (which is required) were rewritten to operate on LTPDA Analysis Objects.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 Univariate and multivariate technique are available, so to estimate for example the linear
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 power spectral density or the cross spectral density of one or more signals. The focus of the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 tools is on time-series objects, whose spectral content needs to be estimated.<br>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 More detailed help on spectral estimation can also be found in the help associated with
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 the Signal Processing Toolbox:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 <table cellspacing="0" class="note" summary="Note" cellpadding="5" border="1">
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12 <tr width="90%">
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13 <td>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 >> doc signal
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15 </td>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 </tr>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 </table>
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18 </p>