Difference between revisions of "Matrices"

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Individual colums and rows are often denoted as column vectors and row vectors. For the example matrix the column vectors are
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Individual colums and rows are often denoted as column vectors and row vectors. For the example matrix <math>\mathbf{A}</math> the column vectors are
 
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Revision as of 15:40, 15 May 2014

This article deals with some fundamental matrix features and the basic arithmetic operations.

Matrices can have arbitrary dimensions. A matrix with m rows and n colums is denoted as an m-by-n matrix. In the context of robotics mainly 3-by-3 or 4-by-4 matrices are used. An example of a 3-by-3 matrix is:


\mathbf{A}=\left[
\begin{array}{ccc}
a_{11} & a_{12} & a_{13}\\
a_{21} & a_{22} & a_{23}\\
a_{31} & a_{32} & a_{33}
\end{array}\right]

Individual colums and rows are often denoted as column vectors and row vectors. For the example matrix \mathbf{A} the column vectors are


\left[
\begin{array}{c}
a_{11}\\
a_{21}\\
a_{31}
\end{array}\right], 
\left[
\begin{array}{c}
a_{12}\\
a_{22}\\
a_{32}
\end{array}\right],\text{and }
\left[
\begin{array}{c}
a_{13}\\
a_{23}\\
a_{33}
\end{array}\right]

and the row vectors are


\left[
\begin{array}{ccc}
a_{11} & a_{12} & a_{13}
\end{array}\right], 
\left[
\begin{array}{ccc}
a_{21} & a_{22} & a_{23}
\end{array}\right],\text{and }
\left[
\begin{array}{ccc}
a_{31} & a_{32} & a_{33}
\end{array}\right]

In the following subarticles some basic arithmetic operations for matrices are described.

  1. The transpose of a matrix
  2. Addition of matrices
  3. Multiplication with a scalar
  4. Multiplication with a vector
  5. Multiplication of matrices