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Difference between revisions of "Matrix"
(→‎Vector spaces associated with a matrix)
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As already stated before, the columns of <math>A</math> form a subset of <math>F^m</math>. The subspace of <math>F^m</math> generated by these columns is said to be the column space of <math>A</math>, written as <math>C(A)</math>. Similarly, the transposes of the rows form a subset of the vector space <math>F^n</math>. The subspace of <math>F^n</math> generated by these is known as the row space of <math>A</math>, written as <math>R(A)</math>.
 
As already stated before, the columns of <math>A</math> form a subset of <math>F^m</math>. The subspace of <math>F^m</math> generated by these columns is said to be the column space of <math>A</math>, written as <math>C(A)</math>. Similarly, the transposes of the rows form a subset of the vector space <math>F^n</math>. The subspace of <math>F^n</math> generated by these is known as the row space of <math>A</math>, written as <math>R(A)</math>.
  
−
<math>y \in C(A) </math>implies <math>\exists x </math> such that <math> y_{m \times 1} = A_{{m \times n} x_{n \times 1}</math>
+
<math>y \in C(A) </math>implies <math>\exists x </math> such that <math> y_{m \times 1} = A_{m \times n} x_{n \times 1}</math>
  
 
== Rank and nullity ==
 
== Rank and nullity ==

Revision as of 07:00, 5 November 2006

A matrix is a rectangular array of scalars from any field, such that each column belongs to the vector space $F^m$, where $m$ is the number of rows. If a matrix $A$ has $m$ rows and $n$ columns, its order is said to be $m \times n$, and it is written as $A_{m \times n}$.

The element in the $i^{th}$ row and $j^{th}$ column of $A$ is written as $(A)_{ij}$. It is more often written as $a_{ij}$, in which case $A$ can be written as $[a_{ij}]$.

Transposes

Let $A$ be $[a_{ij}]$. Then $[a_{ji}]$ is said to be the transpose of $A$, written as $A^T$ or simply $A'$. If A is over the complex field, replacing each element of $A^T$ by its complex conjugate gives us the conjugate transpose $A^*$ of $A$. In other words, $A^*=[\bar {a_{ji}}]$

$A$ is said to be symmetric if and only if $A=A^T$. $A$ is said to be hermitian if and only if $A=A^*$. $A$ is said to be skew symmetric if and only if $A=-A^T$. $A$ is said to be skew hermitian if and only if $A=-A^*$.

Vector spaces associated with a matrix

As already stated before, the columns of $A$ form a subset of $F^m$. The subspace of $F^m$ generated by these columns is said to be the column space of $A$, written as $C(A)$. Similarly, the transposes of the rows form a subset of the vector space $F^n$. The subspace of $F^n$ generated by these is known as the row space of $A$, written as $R(A)$.

$y \in C(A)$implies $\exists x$ such that $y_{m \times 1} = A_{m \times n} x_{n \times 1}$

Rank and nullity

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