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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:29:47 +0100
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  <title>Linear Parameter Estimation with Singular Value Decomposition (LTPDA Toolbox)</title>
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      <td valign="baseline"><b>LTPDA Toolbox</b></td><td><a href="../helptoc.html">contents</a></td>

      <td valign="baseline" align="right"><a href=
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      "bottom" alt="Polynomial Fitting"></a>&nbsp;&nbsp;&nbsp;<a href=
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  <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Linear Parameter Estimation with Singular Value Decomposition</h1>
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  <!-- ================================================== -->
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              <col width="63%"/>
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            <tbody>
              <tr valign="top">
                <td>
                  <a href="#linlsqsvd_1exp">ao/linlsqsvd</a>
                </td>
                <td>Linear least squares with singular value deconposition - single experiment.</td>
              </tr>
              <tr valign="top">
                <td>
                  <a href="#linlsqsvd_Nexp">matrix/linlsqsvd</a>
                </td>
                <td>Linear least squares with singular value deconposition - multiple experiments.</td>
              </tr>
              <tr valign="top">
                <td>
                  <a href="#linfitsvd1">matrix/linfitsvd</a>
                </td>
                <td>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain.</td>
              </tr>
              <tr valign="top">
                <td>
                  <a href="#linfitsvd2">matrix/linfitsvd</a>
                </td>
                <td>Iterative linear parameter estimation for multichannel systems - ssm system model in time domain.</td>
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              <tr valign="top">
                <td>
                  <a href="#ref">References</a>
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  <p>
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  <p>
    The following sections gives an introduction to the linear parameters
    estimation methods based on singular value decomposition.
  </p>

  <!-- ===== ao/linlsqsvd ====== -->
  <h2><a name="#linlsqsvd_1exp">Linear least squares with singular value deconposition - single experiment.</a></h2>
  <p>
    We report an <a href="sigproc_example_ao_linlsqsvd.html">example</a>
    of the application of <a href="matlab:doc('ao/linlsqsvd')">ao/linlsqsvd</a>.
    The <a href="sigproc_example_ao_linlsqsvd.html">example</a> shows how to
    perform a linear parameters estimation for a single data series which is
    representing the output of an experiment on a given physical system.
  </p>
  
  <!-- ===== matrix/linlsqsvd ====== -->
  <h2><a name="#linlsqsvd_Nexp">Linear least squares with singular value deconposition - multiple experiments.</a></h2>
  <p>
    We report an <a href="sigproc_example_matrix_linlsqsvd.html">example</a>
    of the application of <a href="matlab:doc('matrix/linlsqsvd')">matrix/linlsqsvd</a>.
    The <a href="sigproc_example_matrix_linlsqsvd.html">example</a> shows how to
    perform a linear parameters estimation for multiple data series which are
    representing the output of multiple experiments on a given physical system.
  </p>
  
  <!-- ===== matrix/linfitsvd ====== -->
  <h2><a name="#linfitsvd1">Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain.</a></h2>
  <p>
    We report an <a href="sigproc_example_matrix_linfitsvd.html">example</a>
    of the application of <a href="matlab:doc('matrix/linfitsvd')">matrix/linfitsvd</a>.
    The <a href="sigproc_example_matrix_linfitsvd.html">example</a> shows how to
    perform an iterative linear parameters estimation for a multichannel system.
    System model is analystic and frequency domain. Fit is performed in time domain.
    Further details can be found in ref. [1].
  </p>
  
  <!-- ===== matrix/linfitsvd ====== -->
  <h2><a name="#linfitsvd2">Iterative linear parameter estimation for multichannel systems - ssm system model in time domain.</a></h2>
  <p>
    We report an <a href="sigproc_example_matrix_linfitsvd_ssm.html">example</a>
    of the application of <a href="matlab:doc('matrix/linfitsvd')">matrix/linfitsvd</a>.
    The <a href="sigproc_example_matrix_linfitsvd_ssm.html">example</a> shows how to
    perform an iterative linear parameters estimation for a multichannel system.
    System model is ssm and time domain. Fit is performed in time domain.
  </p>
  
  <h2><a name="#ref"> References</a></h2>
  <ol>
    <li> M Nofrarias, L Ferraioli, G Congedo, Comparison of parameter 
    estimates results in STOC Exercise 6, S2-AEI-TN-3070.</li>
  </ol>
  
  
  


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      "Polynomial Fitting"></a>&nbsp;</td>

      <td align="left">Polynomial Fitting</td>

      <td>&nbsp;</td>

      <td align="right">Linear least squares with singular value deconposition - single experiment</td>

      <td align="right" width="20"><a href=
      "sigproc_example_ao_linlsqsvd.html"><img src="b_next.gif" border="0" align=
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