In this note we prove that if

and

are both nonnegative definite Hermitian matrices and

is also nonnegative definite, then the singular values of A and B satisfy the inequalities

, where

denote the singular values of a matrix. A consequence of this property is that, in a nonsquare H^{infty} optimization problem, if
![\\sup_{\\omega } \\bar{\\sigma }[Z(j\\sigma )] {\\underline {\\underline \\Delta }} \\sup_{\\omega } \\bar{\\sigma }[x(j\\omega )^{T}/ Y(j\\omega )^{T}]^{T} = \\lambda](/images/tex/3311.gif)
, then the singular values of

and

satisfy the inequality
![\\lambda ^{2} \\geq \\max _{i} \\sup_{\\omega } [\\sigma _{i}^{2}(X) + \\sigma _{m-i-1}^{2}(Y)]](/images/tex/3312.gif)
where

is the number of columns of the matrix

.