Spectral decomposition of real symmetric quadratic $\lambda $-matrices and its applications
Spectral decomposition of real symmetric quadratic $\lambda $-matrices and its applications
Spectral decomposition provides a canonical representation of an operator over a vector space in terms of its eigenvalues and eigenfunctions. The canonical form often facilitates discussions which, otherwise, would be complicated and involved. Spectral decomposition is of fundamental importance in many applications. The well-known GLR theory generalizes the classical result …