title: Comparing similar sensor signals
body: <p>I have a set of sensor signal samples (containing roughly 10 readings that both contain X,Y and Z axis readings) that I am using as a training set, let's call the set (s1).  The program is constantly listing to sensor signals every 2 seconds which we will call (h1).  Now, what I want to do is use h1 (which contains a single signal reading) and match that against the training set of signals (s1). </p>
  
  <p>So from (s1), the signal that is most similar to (h1) (strong similarities such as signal peak, peak level etc..). </p>
  
  <p>Could this easily be done using Neural Networks? Anything particular to look out for when dealing with signals? fourier transform?</p>
  
  <p>If Neural Networks is the way to go, any particular algorithm that would be ideal with this sort of data.  I'm currently making an application that assesses road surfaces using an accelerometers data.</p>
  
  <p>An example of a signal I am dealing with is this below.</p>
  
  <pre><code>Date= 1/1/2012 (dd:mm:yyyy) Time= 1:45:2 (hh:mm:ss)
  Speed Bump Recording Started at 1:45:2 (hh:mm:ss)
  X-Value = -0.141905, Y-Value = 8.436457, Z-Value = 5.019961, Timestamp(milliseconds) = 75002
  X-Value = -0.218546, Y-Value = 8.244855, Z-Value = 4.828360, Timestamp(milliseconds) = 75201
  X-Value = 0.317939, Y-Value = 8.781339, Z-Value = 4.866680, Timestamp(milliseconds) = 75401
  X-Value = 0.088017, Y-Value = 8.014933, Z-Value = 4.981641, Timestamp(milliseconds) = 75602
  X-Value = 0.011376, Y-Value = 7.976613, Z-Value = 5.633086, Timestamp(milliseconds) = 75802
  X-Value = 0.164658, Y-Value = 8.934620, Z-Value = 4.790039, Timestamp(milliseconds) = 76001
  X-Value = -0.141905, Y-Value = 8.474776, Z-Value = 3.985312, Timestamp(milliseconds) = 76202
  X-Value = 0.432900, Y-Value = 8.781339, Z-Value = 4.636758, Timestamp(milliseconds) = 76402
  X-Value = -0.141905, Y-Value = 9.471105, Z-Value = 4.138594, Timestamp(milliseconds) = 76601
  X-Value = 0.202978, Y-Value = 8.704699, Z-Value = 3.525469, Timestamp(milliseconds) = 76800
  X-Value = 0.394579, Y-Value = 7.440128, Z-Value = 3.640430, Timestamp(milliseconds) = 77001
  X-Value = -0.448467, Y-Value = 6.903644, Z-Value = 4.023633, Timestamp(milliseconds) = 77203
  X-Value = -0.640069, Y-Value = 11.195518, Z-Value = 9.005274, Timestamp(milliseconds) = 77401
  X-Value = -0.065264, Y-Value = 5.945636, Z-Value = 4.176914, Timestamp(milliseconds) = 77604
  X-Value = -0.755030, Y-Value = 9.317823, Z-Value = 4.675078, Timestamp(milliseconds) = 77801
  X-Value = -0.563428, Y-Value = 8.896300, Z-Value = 5.824687, Timestamp(milliseconds) = 78003
  X-Value = -0.410147, Y-Value = 8.014933, Z-Value = 5.211563, Timestamp(milliseconds) = 78201
  X-Value = -0.371827, Y-Value = 8.168214, Z-Value = 5.173242, Timestamp(milliseconds) = 78401
  Speed Bump Recording Stopped at 1:45:6 (hh:mm:ss)
  </code></pre>