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Singular value decomposition
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=== Hilbert–Schmidt norm{{Anchor|Hilbert–Schmidt norm|Hilbert-Schmidt norm|Hilbert–Schmidt|Hilbert-Schmidt}} === The singular values are related to another norm on the space of operators. Consider the [[Hilbert–Schmidt operator|Hilbert–Schmidt]] inner product on the {{tmath|n \times n}} matrices, defined by <math display=block> \langle \mathbf{M}, \mathbf{N} \rangle = \operatorname{tr} \left( \mathbf{N}^*\mathbf{M} \right). </math> So the induced norm is <math display=block> \| \mathbf{M} \| = \sqrt{\langle \mathbf{M}, \mathbf{M} \rangle} = \sqrt{\operatorname{tr} \left( \mathbf{M}^*\mathbf{M} \right)}. </math> Since the trace is invariant under unitary equivalence, this shows <math display=block> \| \mathbf{M} \| = \sqrt{\vphantom\bigg|\sum_i \sigma_i ^2} </math> where {{tmath|\sigma_i}} are the singular values of {{tmath|\mathbf M.}} This is called the '''[[Frobenius norm]]''', '''Schatten 2-norm''', or '''Hilbert–Schmidt norm''' of {{tmath|\mathbf M.}} Direct calculation shows that the Frobenius norm of {{tmath|\mathbf M {{=}} (m_{ij})}} coincides with: <math display=block> \sqrt{\vphantom\bigg|\sum_{ij} | m_{ij} |^2}. </math> In addition, the Frobenius norm and the trace norm (the nuclear norm) are special cases of the [[Schatten norm]].
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