+
−<h2>Description</h2>
+
−<p>
+
−  Spikes in data due to different nature can be removed, if desired, from the original data. LTPDA <a href="matlab:doc('ao/spikecleaning')"><tt>spikecleaning</tt></a> detects and replaces
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−  spikes of the input AOs. A spike in data is defined as a single sample exceeding a certain value (usually, the
+
−  floor noise of the data) defined by the user:
+
−</p>
+
−<br>
+
−<p>
+
−  <div align="center">
+
−    <IMG src="images/spike10x.png" width="147" height="15" border="0" />
+
−  </div>
+
−</p>
+
−<br>
+
−<p>
+
−  where <IMG src="images/spike41x.png" width="50" height="14" border="0" /> is the input data high-pass filtered, <IMG src="images/spike42x.png" width="34" height="13" border="0"/> is a value defined by the user (by default is 3.3) and <IMG src="images/spike43x.png" width="35" height="8" border="0"/> is the standard deviation of <IMG src="images/spike41x.png" width="50" height="14" border="0" /> . In consequence, a spike is defined as the value that exceeds the floor noise of the data by a factor <IMG src="images/spike42x.png" width="34" height="13" border="0"/>, the higher of this parameter the more difficult to "detect" a spike.
+
−  <br>
+
−  <br>
+
−  <h2>Syntax</h2>
+
−</p>
+
−<div class="fragment"><pre>
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−    <br>
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−    b = spikecleaning(a, pl)
+
−  </pre>
+
−</div>
+
−<h2>Parameters</h2>
+
−<p>
+
−  The following parameters can be set in this method:
+
−  <ul>
+
−    <li> <tt>'kspike'</tt> - set the <IMG src="images/spike42x.png" width="34" height="13" border="0"/> value (default is 3.3) </li>
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−    <li> <tt>'method'</tt> - method used to replace the "spiky" sample. Three methods are available ---see below for details---:</li>
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−    <ul>
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−      <li> <tt>'random'</tt> </li>
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−      <li> <tt>'mean'</tt> </li>
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−      <li> <tt>'previous'</tt> </li>
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−    </ul>
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−    <li> <tt>'fc'</tt> - frequency cut-off of the high-pass IIR filter (default is 0.025) </li>
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−    <li> <tt>'order'</tt> - specifies the order of the IIR filter (default is 2) </li>
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−    <li> <tt>'ripple'</tt> - specifies pass/stop-band ripple for bandpass and bandreject filters (default is 0.5) </li>
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−  </ul>
+
−</p>
+
−<p>
+
−  <h2>Algorithm</h2>
+
−</p>
+
−<p>
+
−  <b>Random: </b> this method substitutes the spiky sample by:
+
−</p>
+
−<p>
+
−  <br>
+
−  <div align="center">
+
−    <IMG src="images/spike20x.png" width="197" height="15" align="center" border="0"/>
+
−  </div>
+
−  <br>
+
−</p>
+
−<p>
+
−  where <IMG src="images/spike44x.png" width="42" height="14" border="0"/> is a random number of mean zero and standard deviation 1.
+
−</p>
+
−<p>
+
−  <b>Mean: </b>this method uses the following equation to replace the spike detected in data.
+
−</p>
+
−<br>
+
−<p>
+
−  <div align="center">
+
−    <IMG src="images/spike30x.png" width="158" height="29" align="center" border="0"/>
+
−  </div>  
+
−</p>
+
−<br>
+
−<p>
+
−  <b>Previous: </b>the spike is substitued by the previous sample, i.e.:
+
−</p>
+
−<br>
+
−<p>
+
−  <div align="center">
+
−    <IMG src="images/spike40x.png" width="90" height="14" align="center" border="0"/>
+
−  </div>
+
−</p>
+
−<br>
+
−<p>
+
−  <h2>Examples</h2>
+
−</p>
+
−<p>
+
−  1. Spike cleaning of a sequence of random data with <tt>kspike = 2</tt>.
+
−</p>
+
−<p>
+
−  <div class="fragment"><pre>
+
−      <br>
+
−      x = ao(plist( <span class="string">'waveform'</span>, <span class="string">'noise'</span>, <span class="string">'nsecs'</span>,1e4, <span class="string">'fs'</span>,10)); <span class="comment">% create an AO of random data sampled at 1 Hz.</span>
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−      pl = plist( <span class="string">'kspike'</span>, 2);                         <span class="comment">% kspike = 2</span>
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−      y = spikecleaning(x, pl);                         <span class="comment">% spike cleaning function applied to the input AO, x</span>
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−      iplot(x, y)                                       <span class="comment">% plot original and "cleaned" data</span>
+
−    </pre>
+
−  </div>
+
−</p>
+
−<p>
+
−  <div align="center">
+
−    <img src="images/spike1.png" border="1" >
+
−  </div>
+
−</p>
+
−<!--  <p>
+
−  2. Example of real data: the first image shows data from the real world prior to
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−	   the application of the spike cleaning tool. It is clear that some spikes are
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−	   present in data and might be convenient to remove them. The second image shows
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−	   the same data after the spike samples supression.
+
−  </p>
+
−  <p>
+
−    	<img src="images/stat1x.png" border="1" width="400px">
+
−  </p>
+
−    <p>
+
−    	<img src="images/stat2x.png" border="1" width="400px">
+
−  </p>
+
− -->
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−
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−