Spectral Norm from Eigenvalue Decomposition
DESCRIPTION:
Computes the spectral (2) norm of a matrix given its singular-value decomposition.
USAGE: 
norm.svd.Matrix(x)
REQUIRED ARGUMENTS:
x:
An object of class "svd.Matrix" representing the singular value decomposition of a numeric or complex Matrix.
VALUE:
An object of class "norm" representing the spectral or 2 norm of the matrix underlying x. A copy of the call to norm is returned as an attribute.
DETAILS:
The spectral or 2 norm of a matrix is equal to its largest singular value.
REFERENCES:
Golub, G., and Van Loan, C. F. (1989). Matrix Computations, 2nd edition, Johns Hopkins, Baltimore.
SEE ALSO:
svd , norm.Matrix , norm.eigen.Hermitian .
EXAMPLES: 
x <- Matrix( sample(-3:3, size = 9, replace = T), nrow = 3, ncol = 3)
norm(svd(x))