Matrix

For the 1999 film, see The Matrix.

A matrix (pl.: "matrices," Latin origin) is a complex ordering, in deliberate fashion, of numerals. In mathematics, a "matrix" is a regular grid of numbers, which may be manipulated and solved through intermediate-level algebra. Matrix algebra is usually taught in sophomore high school level mathematics.

More formally, a matrix is an example of a rank-2 tensor.

Alternately, a matrix may also be a complex ordering of a group of equivalent objects, especially where the order is imposed to gain incidental benefit from the synergy of the networked objects.

Mathematics

In mathematics, matrices can be manipulated in a variety of ways, including addition and multiplication.

Addition of matrices

To add two matrices, one would add their respective elements. For example:

${\begin{bmatrix}x&y&z\\1&3&5\\0&2&0\end{bmatrix}}+{\begin{bmatrix}0&3&1\\4&3&{x+2}\\0&4&v\end{bmatrix}}$

would equal

${\begin{bmatrix}{x+0}&{y+3}&{z+1}\\{1+4}&{3+3}&{5+(x+2)}\\{0+0}&{2+4}&{0+v}\end{bmatrix}}={\begin{bmatrix}x&{y+3}&{z+1}\\5&6&{x+7}\\0&6&v\end{bmatrix}}$

Multiplication of matrices

To multiply two matrices, use the rule for finding the product of two matrices:

$(AB)_{ij}=\sum _{k}A_{ik}B_{kj}$

However, not every pair of matrices can be multiplied. In order for matrices $A$ and $B$ to be compatible for multiplication, the number of columns in $A$ must equal the number of rows in $B$. If $A$ is an $m\times n$ matrix and $B$ is an $n\times p$ matrix, the product matrix $AB$ will have $m$ rows and $p$ columns.

Matrix multiplication is associative. However, matrix multiplication is not commutative. That is, it is possible for $AB\neq BA$.

Matrix concepts

Basic concepts

• Adjoint
• Determinant
• Diagonal matrix
• Identity matrix
• Inverse matrix
• Null, column and row space
• Scalar
• Trace
• Transpose matrix
• Vector
• Zero matrix

Advanced concepts

• Basis
• Diagonalizable
• Eigenspace
• Eigenvalue
• Eigenvector
• Gram-Schmidt process
• Hermitian matrix
• Jordan canonical form
• Laplacian
• Linear independence
• Matrix diagonalization
• Matrix reformation
• Matrix transformation
• Orthogonal matrix
• Orthonormal matrix
• Resultant
• Span
• Systems of linear equations
• Transcriptor
• Wronskian