In mathematics, in particular functional analysis, the singular values, or s-numbers of a compact operator T : X → Y acting between Hilbert spaces X and Y, are the square roots of non-negative eigenvalues of the self-adjoint operator T*T (where T* denotes the adjoint of T).
In the case that T acts on euclidean space Rn, there is a simple geometric interpretation for the singular values: Consider the image by T of the unit sphere; this is an ellipsoid, and the lengths of its semi-axes are the singular values of T (the figure provides an example in R2).
Most norms on Hilbert space operators studied are defined using s-numbers. For example, the Ky Fan-k-norm is the sum of first k singular values, the trace norm is the sum of all singular values, and the Schatten norm is the pth root of the sum of the pth powers of the singular values. Note that each norm is defined only on a special class of operators, hence s-numbers are useful in classifying different operators.
In the finite-dimensional case, a matrix can always be decomposed in the form UΣV*, where U and V* are unitary matrices and Σ is a diagonal matrix with the singular values lying on the diagonal. This is the singular value decomposition.
For and .
Min-max theorem for singular values. Here is a subspace of of dimension .
Matrix transpose and conjugate do not alter singular values.
For any unitary
Relation to eigenvalues:
Inequalities about singular values
Singular values of sub-matrices
with one of its rows or columns deleted. Then
with one of its rows and columns deleted. Then
Singular values of
Singular values and eigenvalues
. Then for
- Weyl's theorem
- Weyl's theorem
This concept was introduced by Erhard Schmidt in 1907. Schmidt called singular values "eigenvalues" at that time. The name "singular value" was first quoted by Smithies in 1937. In 1957, Allahverdiev proved the following characterization of the nth s-number :
This formulation made it possible to extend the notion of s-numbers to operators in Banach space.
- R.A. Horn and C.R. Johnson. Topics in Matrix Analysis. Cambridge University Press, Cambridge, 1991. Chap. 3
- X. Zhan. Matrix Inequalities. Springer-Verlag, Berlin, Heidelberg, 2002. p.28
- R. Bhatia. Matrix Analysis. Springer-Verlag, New York, 1997. Prop. III.5.1