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		<id>https://en.formulasearchengine.com/w/index.php?title=Friction_loss&amp;diff=15091</id>
		<title>Friction loss</title>
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		<summary type="html">&lt;p&gt;213.216.144.200: Deleted section on firefighting. Not relevant to the article and is incorrect in what it says anyway.&lt;/p&gt;
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&lt;div&gt;In [[mathematics]], especially in [[linear algebra]] and [[Matrix (mathematics)|matrix theory]], the &#039;&#039;&#039;duplication matrix&#039;&#039;&#039; and the &#039;&#039;&#039;elimination matrix&#039;&#039;&#039; are [[linear transformation]]s used for transforming [[vectorization (mathematics)#Half-vectorization|half-vectorization]]s of [[matrix (mathematics)|matrices]] into [[vectorization (mathematics)|vectorizations]] or (respectively) vice-versa.&lt;br /&gt;
&lt;br /&gt;
==Duplication matrix==&lt;br /&gt;
The duplication matrix &#039;&#039;D&#039;&#039;&amp;lt;sub&amp;gt;&#039;&#039;n&#039;&#039;&amp;lt;/sup&amp;gt; is the unique &#039;&#039;n&#039;&#039;&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; × &#039;&#039;n&#039;&#039;(&#039;&#039;n&#039;&#039;+1)/2 matrix which, for any &#039;&#039;n&#039;&#039; × &#039;&#039;n&#039;&#039; [[symmetric matrix]] &#039;&#039;A&#039;&#039;, transforms vech(&#039;&#039;A&#039;&#039;) into vec(&#039;&#039;A&#039;&#039;):&lt;br /&gt;
:&#039;&#039;D&#039;&#039;&amp;lt;sub&amp;gt;n&amp;lt;/sub&amp;gt; vech(&#039;&#039;A&#039;&#039;) = vec(&#039;&#039;A&#039;&#039;).&lt;br /&gt;
&lt;br /&gt;
For the 2×2 symmetric matrix &#039;&#039;A&#039;&#039; = &amp;lt;math&amp;gt;\left[\begin{smallmatrix} a &amp;amp; b \\ b &amp;amp; d \end{smallmatrix}\right]&amp;lt;/math&amp;gt;, this transformation reads&lt;br /&gt;
: &amp;lt;math&amp;gt;\begin{bmatrix} 1&amp;amp;0&amp;amp;0 \\ 0&amp;amp;1&amp;amp;0 \\ 0&amp;amp;1&amp;amp;0 \\ 0&amp;amp;0&amp;amp;1 \end{bmatrix} \begin{bmatrix} a \\ b \\ d \end{bmatrix} = \begin{bmatrix} a \\ b \\ b \\ d \end{bmatrix}&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
==Elimination matrix==&lt;br /&gt;
The elimination matrix &#039;&#039;L&#039;&#039;&amp;lt;sub&amp;gt;&#039;&#039;n&#039;&#039;&amp;lt;/sup&amp;gt; is the unique &#039;&#039;n&#039;&#039;(&#039;&#039;n&#039;&#039;+1)/2 × &#039;&#039;n&#039;&#039;&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; matrix which, for any &#039;&#039;n&#039;&#039; × &#039;&#039;n&#039;&#039; matrix &#039;&#039;A&#039;&#039;, transforms vec(&#039;&#039;A&#039;&#039;) into vech(&#039;&#039;A&#039;&#039;):&lt;br /&gt;
:&#039;&#039;L&#039;&#039;&amp;lt;sub&amp;gt;n&amp;lt;/sub&amp;gt; vec(&#039;&#039;A&#039;&#039;) = vech(&#039;&#039;A&#039;&#039;).&amp;amp;nbsp;&amp;lt;ref&amp;gt;{{harvtxt|Magnus|Neudecker|1980}}, Definition 3.1&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
For the 2×2 matrix &#039;&#039;A&#039;&#039; = &amp;lt;math&amp;gt;\left[\begin{smallmatrix} a &amp;amp; b \\ c &amp;amp; d \end{smallmatrix}\right]&amp;lt;/math&amp;gt;, this transformation reads&lt;br /&gt;
: &amp;lt;math&amp;gt;\begin{bmatrix} 1&amp;amp;0&amp;amp;0&amp;amp;0 \\ 0&amp;amp;1&amp;amp;0&amp;amp;0 \\ 0&amp;amp;0&amp;amp;0&amp;amp;1 \end{bmatrix} \begin{bmatrix} a \\ c \\ b \\ d \end{bmatrix} = \begin{bmatrix} a \\ c \\ d \end{bmatrix}&amp;lt;/math&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
==Notes==&lt;br /&gt;
&amp;lt;references/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
*{{Citation | last1=Magnus | first1=Jan R. | last2=Neudecker | first2=Heinz | title=The elimination matrix: some lemmas and applications | doi=10.1137/0601049 | year=1980 | journal=Society for Industrial and Applied Mathematics. Journal on Algebraic and Discrete Methods | issn=0196-5212 | volume=1 | issue=4 | pages=422–449}}.&lt;br /&gt;
*Jan R. Magnus and Heinz Neudecker (1988), &#039;&#039;Matrix Differential Calculus with Applications in Statistics and Econometrics&#039;&#039;, Wiley. ISBN 0-471-98633-X.&lt;br /&gt;
*Jan R. Magnus (1988), &#039;&#039;Linear Structures&#039;&#039;, Oxford University Press. ISBN 0-19-520655-X &lt;br /&gt;
&lt;br /&gt;
[[Category:Matrices]]&lt;br /&gt;
&lt;br /&gt;
[[de:Eliminationsmatrix]]&lt;/div&gt;</summary>
		<author><name>213.216.144.200</name></author>
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