title: Svd recomposition with Mathnet numerics library seems wrong
body: <p>I'm looking for non regression between Mathnet.Iridium and Mathnet.Numerics. Here is my code, using Mathnet.Numerics :</p>
  
  <pre><code>double[][] symJaggedArray = new double[5][];
  symJaggedArray[0] = new double[] { 3, 0, 0, 0, 0 };
  symJaggedArray[1] = new double[] { 0, 2, 4, 0, 0 };
  symJaggedArray[2] = new double[] { 0, 4, 5, -4, 5 };
  symJaggedArray[3] = new double[] { 0, 0, -4, -8, 12 };
  symJaggedArray[4] = new double[] { 0, 0, 5, 12, -5 };
  symDenseMatrix = DenseMatrix.OfArray(new Matrix(symJaggedArray).CopyToArray());// not optimal but it's not the point
  
  Svd svd = new UserSvd(symDenseMatrix , true);
  Matrix&lt;double&gt; recompo = svd.U().Multiply(svd.W()).Multiply(svd.VT());
  </code></pre>
  
  <p>When i compare recompo and the initial matrix, they are different.
  I found this difference when comparing each decomposition matrix with the previous implementation :</p>
  
  <ul>
  <li>U and singularValueDecomposition.LeftSingularVectors are equal</li>
  <li>W and singularValueDecomposition.S are equal</li>
  <li>VT and Matrix.Transpose(singulaValueDecomposition.RightSingularVectors) are different</li>
  </ul>
  
  <p>Finally, recomposition with older API is correct.</p>
  
  <p>MathNet.Numerics version used : Math.NET Numerics v2.5.0</p>
  
  <p>So my question is : Where is my mistake when rebuilding initial matrix with the new API ?</p>
  
  <p>RecompoMatrix = </p>
  
  <ul>
  <li>3 0 0 0 0 </li>
  <li>0 -1.216846655456 2.83903817786199 1.4472680220698 2.89215520227421</li>
  <li>0 -2.46695399700557 8.657344064164 0.92863757484644 -0.31963101527516</li>
  <li>0 0.349540484418384 8.20515629935223 -2.26741625715781 -12.3049605878983</li>
  <li>0 -0.402667067831389 -6.32914150795323 9.13315298351198 8.3884053064068</li>
  </ul>