Chapter 10 Eigenvalues and Singular Values

← Back to document page

Chapter 10Eigenvalues and SingularValuesThis Chapter is about Eigenvalues and Singular Values of matrices. Computationalalgorithms and sensitivity to perturbations are both Eigenvalue and Singular Value DecompositionsAneigenvalueandeigenvector of a square matrixAare a scalar and a nonzerovectorxso thatAx= valueand pair ofsingular vectorsof a square or rectangular matrixAare a nonnegative scalar and two nonzero vectorsuandvso thatAv= u,AHu= superscript onAHstands forHermitian transposeand denotes the complexconjugate transpose of a complex matrix. If the matrix is real, thenATdenotes thesame matrix. InMatlab, these transposed matrices are denoted byA'.

of vibration, or critical values of stability parameters, or energy levels of atoms. Singular values play an important role where the matrix is a transformation from one vector space to a different vector space, possibly with a different dimension. ... m-by-n matrix A is thought of as mapping n-space onto m-space. We try to find

  Thought, Vibration