Difference between revisions of "Manuals/calci/MATRIXTENSORPRODUCT"

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<div style="font-size:30px">'''MATRIXTENSORPRODUCT (a,b) '''</div><br/>
+
<div style="font-size:25px">'''MATRIXTENSORPRODUCT (a,b) '''</div><br/>
 
*<math>a</math> and <math>b</math> are any two matrices.
 
*<math>a</math> and <math>b</math> are any two matrices.
  
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*The Tensor product is defined by the product  two vector spaces V and W is itself a Vector space.
 
*The Tensor product is defined by the product  two vector spaces V and W is itself a Vector space.
 
*It is denoted by <math>V\otimes W</math>.  
 
*It is denoted by <math>V\otimes W</math>.  
 +
*A [http://wiki.zcubes.com/Manuals/calci/DYADIC DYADIC] product is the special case of the tensor product between two vectors of the same dimension.
 
*The tensor product of V and W is the vector space generated by the symbols  <math>v\otimes w </math>, with  <math>v \isin V</math> and <math>w \isin W</math>.
 
*The tensor product of V and W is the vector space generated by the symbols  <math>v\otimes w </math>, with  <math>v \isin V</math> and <math>w \isin W</math>.
 
*The tensor product from the direct sum vector space, whose dimension is the sum of the dimensions of the two summands:
 
*The tensor product from the direct sum vector space, whose dimension is the sum of the dimensions of the two summands:
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b_{21} & b_{22}  
 
b_{21} & b_{22}  
 
\end{bmatrix} \\
 
\end{bmatrix} \\
 +
 
a_{21} \begin{bmatrix}
 
a_{21} \begin{bmatrix}
 
b_{11}      & b_{12}    \\
 
b_{11}      & b_{12}    \\
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\end{bmatrix} </math> =
 
\end{bmatrix} </math> =
 
<math>\begin{bmatrix}
 
<math>\begin{bmatrix}
a_{11}b_{11}  a_{11}b_{12} a_{12}b_{11} a_{12}b_{12}\\
+
a_{11}b_{11} & a_{11}b_{12} & a_{12}b_{11} & a_{12}b_{12}\\
 +
a_{11}b_{21} & a_{11}b_{22} & a_{12}b_{21} & a_{12}b_{22}\\
 +
a_{21}b_{11} & a_{21}b_{12} & a_{22}b_{11} & a_{22}b_{12}\\
 +
a_{21}b_{21} & a_{21}b_{22} & a_{22}b_{21} & a_{22}b_{22}
 
\end{bmatrix} </math>
 
\end{bmatrix} </math>
 +
 +
==Examples==
 +
1. MATRIXTENSORPRODUCT([[2,6],[-4,9]],[[8,5],[3,12]])
 +
{| class="wikitable"
 +
|-
 +
|16 ||10 ||48 ||30
 +
|-
 +
|6 ||24 ||18|| 72
 +
|-
 +
| -32|| -20 || 72||45
 +
|-
 +
| -12 || -48 || 27 ||108
 +
|}
 +
2. MATRIXTENSORPRODUCT([[3,7.3,6],[10,11,-6],[8,5,3]],[[12,4,-5],[6,10,3],[3.5,9,5.4]])
 +
{| class="wikitable"
 +
|-
 +
|36 || 12|| -15 ||87.6 ||29.2||-36.5||72||24||-30
 +
|-
 +
|18 || 30 ||9 ||43.8|| 73||21.9||36|| 60|| 18
 +
|-
 +
|10.5 ||27||16.200000000000003||25.55|| 65.7||39.42||21||54||32.400000000000006
 +
|-
 +
|120 || 40||-50||132||44||-55|| -72||-24||30
 +
|-
 +
|60 || 100||30 ||66 || 110 || 33 || -36 ||-60 ||-18
 +
|-
 +
|35 || 90 || 54 ||38.5||99 ||59.400000000000006 || -21||-54||-32.400000000000006
 +
|-
 +
|96 || 32 || -40 || 60 || 20 || -25 || 36 || 12 ||-15
 +
|-
 +
|48 || 80 ||24 || 30 || 50 || 15 || 18 || 30 ||9
 +
|-
 +
|28 || 72 || 43.2 || 17.5 || 45 ||27 ||10.5 || 27||16.200000000000003
 +
|}
 +
 +
==Related Videos==
 +
 +
{{#ev:youtube|v=tpL95Sd7zT0&t=81s|280|center|Tensor Product}}
 +
 +
==See Also==
 +
*[[Manuals/calci/CHOLESKYFACTORIZATION| CHOLESKYFACTORIZATION]]
 +
*[[Manuals/calci/CONFERENCE| CONFERENCE]]
 +
*[[Manuals/calci/PASCAL| PASCAL]]
 +
 +
==References==
 +
*[https://en.wikipedia.org/wiki/Tensor_product  Tensor Product]
 +
 +
*[[Z_API_Functions | List of Main Z Functions]]
 +
 +
*[[ Z3 |  Z3 home ]]

Latest revision as of 13:33, 29 April 2019

MATRIXTENSORPRODUCT (a,b)


  • and are any two matrices.

Description

  • This function shows the Tensor product of the matrix.
  • In , and are any two matrices.
  • Here matrices and should be square matrix with same order.
  • Tensor product is denoted by .
  • Tensor product is different from general product.
  • The Tensor product is defined by the product two vector spaces V and W is itself a Vector space.
  • It is denoted by .
  • A DYADIC product is the special case of the tensor product between two vectors of the same dimension.
  • The tensor product of V and W is the vector space generated by the symbols , with and .
  • The tensor product from the direct sum vector space, whose dimension is the sum of the dimensions of the two summands:

  • Now consider any 2x2 matrices:

=

Examples

1. MATRIXTENSORPRODUCT([[2,6],[-4,9]],[[8,5],[3,12]])

16 10 48 30
6 24 18 72
-32 -20 72 45
-12 -48 27 108

2. MATRIXTENSORPRODUCT([[3,7.3,6],[10,11,-6],[8,5,3]],[[12,4,-5],[6,10,3],[3.5,9,5.4]])

36 12 -15 87.6 29.2 -36.5 72 24 -30
18 30 9 43.8 73 21.9 36 60 18
10.5 27 16.200000000000003 25.55 65.7 39.42 21 54 32.400000000000006
120 40 -50 132 44 -55 -72 -24 30
60 100 30 66 110 33 -36 -60 -18
35 90 54 38.5 99 59.400000000000006 -21 -54 -32.400000000000006
96 32 -40 60 20 -25 36 12 -15
48 80 24 30 50 15 18 30 9
28 72 43.2 17.5 45 27 10.5 27 16.200000000000003

Related Videos

Tensor Product

See Also

References