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Compression (functional analysis)
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Compression (functional analysis) : ウィキペディア英語版
Compression (functional analysis)
In functional analysis, the compression of a linear operator ''T'' on a Hilbert space to a subspace ''K'' is the operator
:P_K T \vert_K : K \rightarrow K ,
where P_K : H \rightarrow K is the orthogonal projection onto ''K''. This is a natural way to obtain an operator on ''K'' from an operator on the whole Hilbert space. If ''K'' is an invariant subspace for ''T'', then the compression of ''T'' to ''K'' is the restricted operator ''K→K'' sending ''k'' to ''Tk''.
More generally, for a linear operator ''T'' on a Hilbert space H and an isometry ''V'' on a subspace W of H, define the compression of ''T'' to W by
:T_W = V^
*TV : W \rightarrow W,
where V^
* is the adjoint of ''V''. If ''T'' is a self-adjoint operator, then the compression T_W is also self-adjoint.
When ''V'' is replaced by the identity function I: W \to H, V^
* = I^
*=P_K : H \to W, and we acquire the special definition above.
==See also==

* Dilation

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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