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  • Operations on matrices

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  • Addition
  • Conjugation
  • Scalar multiplication
  • Row operations
  • Matrix-vector products
  • Multiplication
  • Transpose and adjoint
  • Inverse

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  • Definition of matrix multiplication in terms of column vectors
  • Definition of matrix multiplication
  • Theorem describing matrix multiplication
  • Any matrix times the 0 matrix equals the 0 matrix.
  • Example of multiplying 2x2 matrices
  • Example of multiplying 3x3 matrices
  • Example of multiplying nonsquare matrices
  • Example of multiplying matrices
  • Matrix multiplication is associative.
  • Matrix multiplication is distributive over matrix addition.
  • The identity matrix is the identity for matrix multiplication.
  • Matrix multiplication is not commutative in general.
  • For matrices
  • Matrix multiplication can be viewed as the dot product of a row vector of column vectors with a column vector of row vectors
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Description:Added matrix multiplication
# Multiplication

Put content here.**Definition:** The **product** of an $m \times n$ matrix $A$ and an $n \times p$ matrix $B$ is the $m \times p$ matrix $C = AB$ defined by:
⏎
$$c_{ij} = \sum_{k=1}^{n} a_{ik} b_{kj}$$
⏎
The entry $c_{ij}$ is the **dot product** of row $i$ of $A$ with column $j$ of $B$.
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**Example:**
$$\begin{pmatrix} 1 & 2 \\ 3 & 4 \end{pmatrix} \begin{pmatrix} 5 & 6 \\ 7 & 8 \end{pmatrix} = \begin{pmatrix} 19 & 22 \\ 43 & 50 \end{pmatrix}$$
⏎
**Properties:**
- Associative: $(AB)C = A(BC)$
- Distributive: $A(B + C) = AB + AC$
- Identity: $AI = IA = A$
- **NOT commutative**: In general, $AB \neq BA$
⏎
**Important notes:**
- Requires the number of columns of $A$ to equal the number of rows of $B$
- $(AB)^T = B^T A^T$
- $\det(AB) = \det(A)\det(B)$ for square matrices

# Parents

* Operations on matrices
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