10. Further Definitions of Matrix
1) Transposed Matrix: row와 column 바꾸기
$ \vec{\lambda} _{ij}^{t}=\vec{\lambda}_{ji} $
$ (\vec{\lambda}^{t})^{t}=\vec{\lambda} $
$ (\vec{A}\vec{B})^{t}=\vec{B}^{t}\vec{A}^{t} $
ex) Inverse Transformation
$ x_{i}=\sum_{j}^{}\lambda _{ji}x_{j}' $
$ x_{i}=\sum_{j}^{}\lambda _{ij}^{t}x_{j}' $
$ \vec{X}=\vec{\lambda }^{t}\vec{X}' $
$ \bigl(\begin{smallmatrix}
x_{1}\\ x_{2}
\\ x_{3}
\end{smallmatrix}\bigr)=\bigl(\begin{smallmatrix}
\lambda _{11} & \lambda _{21} & \lambda _{31}\\
\lambda _{12} & \lambda _{22} & \lambda _{32}\\
\lambda _{13} & \lambda _{23} & \lambda _{33}
\end{smallmatrix}\bigr) \bigl(\begin{smallmatrix}
x_{1}' \\ x_{2}'
\\ x_{3}'
\end{smallmatrix}\bigr) $
2) Identity Matrix: 매트릭스를 곱해도 변화 x
$ \vec{1}\vec{A}=\vec{A}, \vec{A}\vec{1}=\vec{A} $
$ \bigl(\begin{smallmatrix}
1 & 0 \\
0 & 1
\end{smallmatrix}\bigr) $ in 2x2
ex)
$ \vec{1}\vec{A}=\bigl(\begin{smallmatrix}
1 & 0 \\
0 & 1
\end{smallmatrix}\bigr) \binom{A_{1}}{A_{2}}=\binom{A_{1}}{A_{2}}=\vec{A} $
3) Inverse Matrix: 인벌스를 곱하면 아이덴터티
$ \vec{\lambda }\vec{\lambda }^{-1}=\vec{1} $
11. Orthogonal Matrix
$ \vec{\lambda }=\bigl(\begin{smallmatrix}
\lambda _{11} & \lambda _{12}\\
\lambda _{21} & \lambda _{22}
\end{smallmatrix}\bigr) $: orthogonal rotation matrix of two dimensions
$ \vec{\lambda }\vec{\lambda^{t}}=\bigl(\begin{smallmatrix}
\lambda _{11} & \lambda _{12}\\
\lambda _{21} & \lambda _{22}
\end{smallmatrix}\bigr) \bigl(\begin{smallmatrix}
\lambda _{11} & \lambda _{21}\\
\lambda _{12} & \lambda _{22}
\end{smallmatrix}\bigr)=\bigl(\begin{smallmatrix}
\lambda _{11}^{2}+\lambda _{12}^{2} & \lambda _{11}\lambda _{21}+\lambda _{12}\lambda _{22}\\
\lambda _{21}\lambda _{11}+\lambda _{22}\lambda _{12} & \lambda _{21}^{2}+\lambda _{22}^{2}
\end{smallmatrix}\bigr) $
orthononality relaion
$ \lambda _{11}^{2}+\lambda _{12}^{2}=\lambda _{21}^{2}+\lambda _{22}^{2}=1 $
$ \lambda _{11}\lambda _{21}+\lambda _{12}\lambda _{22}=\lambda _{21}\lambda _{11}+\lambda _{22}\lambda _{12}=0 $
$ \Rightarrow \vec{\lambda }\vec{\lambda^{t}}=\bigl(\begin{smallmatrix}
1 & 0 \\
0 & 1
\end{smallmatrix}\bigr)=\vec{1} $
$ \Rightarrow \vec{\lambda^{t}}=\vec{\lambda}^{-1} $
12. Rules of Matrix Algebra
1) Non commutative (in general)
$ \vec{A}\vec{B}\neq \vec{B}\vec{A} $
but $ \vec{A}\vec{A}^{-1}= \vec{A}^{-1}\vec{A}=\vec{1} $
and $ \vec{1}\vec{A}=\vec{A}\vec{1}=\vec{A} $
2) Associative
$ [\vec{A}\vec{B}]\vec{C}=\vec{A}[\vec{B}\vec{C}] $
3) $ C_{ij}=A_{ij}+B_{ij} $
$ \vec{C}=\vec{A}+\vec{B} $
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