diff --git a/Eigen/src/QR/EigenSolver.h b/Eigen/src/QR/EigenSolver.h
index 44917d139..1b392cbb9 100644
--- a/Eigen/src/QR/EigenSolver.h
+++ b/Eigen/src/QR/EigenSolver.h
@@ -58,9 +58,50 @@ template<typename _MatrixType> class EigenSolver
       compute(matrix);
     }
 
-    MatrixType eigenvectors(void) const { return m_eivec; }
+    // TODO compute the complex eigen vectors
+    // MatrixType eigenvectors(void) const { return m_eivec; }
 
-    EigenvalueType eigenvalues(void) const { return m_eivalues; }
+    /** \returns a real matrix V of pseudo eigenvectors.
+      *
+      * Let D be the block diagonal matrix with the real eigenvalues in 1x1 blocks,
+      * and any complex values u+iv in 2x2 blocks [u v ; -v u]. Then, the matrices D
+      * and V satisfy A*V = V*D.
+      *
+      * More precisely, if the diagonal matrix of the eigen values is:\n
+      * \f$
+      * \left[ \begin{array}{cccccc}
+      * u+iv &      &      &      &   &   \\
+      *      & u-iv &      &      &   &   \\
+      *      &      & a+ib &      &   &   \\
+      *      &      &      & a-ib &   &   \\
+      *      &      &      &      & x &   \\
+      *      &      &      &      &   & y \\
+      * \end{array} \right]
+      * \f$ \n
+      * then, we have:\n
+      * \f$
+      * D =\left[ \begin{array}{cccccc}
+      *  u & v &    &   &   &   \\
+      * -v & u &    &   &   &   \\
+      *    &   &  a & b &   &   \\
+      *    &   & -b & a &   &   \\
+      *    &   &    &   & x &   \\
+      *    &   &    &   &   & y \\
+      * \end{array} \right]
+      * \f$
+      *
+      * \sa pseudoEigenvalueMatrix()
+      */
+    const MatrixType& pseudoEigenvectors() const { return m_eivec; }
+
+    /** \returns the real block diagonal matrix D of the eigenvalues.
+      *
+      * See pseudoEigenvectors() for the details.
+      */
+    MatrixType pseudoEigenvalueMatrix() const;
+
+    /** \returns the eigenvalues as a column vector */
+    EigenvalueType eigenvalues() const { return m_eivalues; }
 
     void compute(const MatrixType& matrix);
 
@@ -74,6 +115,25 @@ template<typename _MatrixType> class EigenSolver
     EigenvalueType m_eivalues;
 };
 
+template<typename MatrixType>
+MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
+{
+  int n = m_eivec.cols();
+  MatrixType matD = MatrixType::Zero(n,n);
+  for (int i=0; i<n; i++)
+  {
+    if (ei_isMuchSmallerThan(ei_imag(m_eivalues.coeff(i)), ei_real(m_eivalues.coeff(i))))
+      matD.coeffRef(i,i) = ei_real(m_eivalues.coeff(i));
+    else
+    {
+      matD.template block<2,2>(i,i) <<  ei_real(m_eivalues.coeff(i)), ei_imag(m_eivalues.coeff(i)),
+                                       -ei_imag(m_eivalues.coeff(i)), ei_real(m_eivalues.coeff(i));
+      i++;
+    }
+  }
+  return matD;
+}
+
 template<typename MatrixType>
 void EigenSolver<MatrixType>::compute(const MatrixType& matrix)
 {
diff --git a/test/eigensolver.cpp b/test/eigensolver.cpp
index beccdc321..9ede071f0 100644
--- a/test/eigensolver.cpp
+++ b/test/eigensolver.cpp
@@ -29,7 +29,7 @@
 #include "gsl_helper.h"
 #endif
 
-template<typename MatrixType> void eigensolver(const MatrixType& m)
+template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
 {
   /* this test covers the following files:
      EigenSolver.h, SelfAdjointEigenSolver.h (and indirectly: Tridiagonalization.h)
@@ -69,11 +69,11 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
     convert<MatrixType>(symmB, gSymmB);
     convert<MatrixType>(symmA, gEvec);
     gEval = GslTraits<RealScalar>::createVector(rows);
-    
+
     Gsl::eigen_symm(gSymmA, gEval, gEvec);
     convert(gEval, _eval);
     convert(gEvec, _evec);
-    
+
     // test gsl itself !
     VERIFY((symmA * _evec).isApprox(_evec * _eval.asDiagonal().eval(), largerEps));
 
@@ -108,13 +108,40 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
   VERIFY((symmA * eiSymmGen.eigenvectors()).isApprox(
           symmB * (eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal().eval()), largerEps));
 
-//   EigenSolver<MatrixType> eiNotSymmButSymm(covMat);
-//   VERIFY_IS_APPROX((covMat.template cast<Complex>()) * (eiNotSymmButSymm.eigenvectors().template cast<Complex>()),
-//     (eiNotSymmButSymm.eigenvectors().template cast<Complex>()) * (eiNotSymmButSymm.eigenvalues().asDiagonal()));
+}
 
-//   EigenSolver<MatrixType> eiNotSymm(a);
-//   VERIFY_IS_APPROX(a.template cast<Complex>() * eiNotSymm.eigenvectors().template cast<Complex>(),
-//     eiNotSymm.eigenvectors().template cast<Complex>() * eiNotSymm.eigenvalues().asDiagonal());
+template<typename MatrixType> void eigensolver(const MatrixType& m)
+{
+  /* this test covers the following files:
+     EigenSolver.h
+  */
+  int rows = m.rows();
+  int cols = m.cols();
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
+  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
+
+  RealScalar largerEps = 10*test_precision<RealScalar>();
+
+  MatrixType a = MatrixType::Random(rows,cols);
+  MatrixType a1 = MatrixType::Random(rows,cols);
+  MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
+
+//   MatrixType b = MatrixType::Random(rows,cols);
+//   MatrixType b1 = MatrixType::Random(rows,cols);
+//   MatrixType symmB = b.adjoint() * b + b1.adjoint() * b1;
+
+  EigenSolver<MatrixType> ei0(symmA);
+  VERIFY_IS_APPROX((symmA.template cast<Complex>()) * (ei0.pseudoEigenvectors().template cast<Complex>()),
+    (ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal()));
+
+  a = a + symmA;
+  EigenSolver<MatrixType> ei1(a);
+
+  VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
 
 }
 
@@ -122,10 +149,12 @@ void test_eigensolver()
 {
   for(int i = 0; i < g_repeat; i++) {
     // very important to test a 3x3 matrix since we provide a special path for it
-    CALL_SUBTEST( eigensolver(Matrix3f()) );
+    CALL_SUBTEST( selfadjointeigensolver(Matrix3f()) );
+    CALL_SUBTEST( selfadjointeigensolver(Matrix4d()) );
+    CALL_SUBTEST( selfadjointeigensolver(MatrixXf(7,7)) );
+    CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(5,5)) );
+    CALL_SUBTEST( selfadjointeigensolver(MatrixXd(19,19)) );
+
     CALL_SUBTEST( eigensolver(Matrix4d()) );
-    CALL_SUBTEST( eigensolver(MatrixXf(7,7)) );
-    CALL_SUBTEST( eigensolver(MatrixXcd(5,5)) );
-    CALL_SUBTEST( eigensolver(MatrixXd(19,19)) );
   }
 }