About
The norm of a vector v is written <math>\left \| v \right \|</math>
Definition
The norm of a vector v is defined by: <MATH>\left \| v \right \| = \sqrt{\left \langle v,v \right \rangle}</MATH>
where:
- <math>\langle v,v \rangle</math> is the inner product of v.
Euclidean space
In Euclidean space, the inner product is the Linear Algebra - Vector Vector Operations.
<math> \begin{array}{crl} v & = &[v_1, v_2, \dots , v_n] \\ \left \| v \right \| & = & \left \| [v_1, v_2, . . . , v_n] \right \| \\ \left \| v \right \| & = & \sqrt{ {v_1}^2 + {v_2}^2 + \dots + {v_n}^2}\\ \left \| v \right \| & = & \sqrt{ \sum v^2_i }\\ \end{array} </math>
For a 2-vector:
<math>
\begin{array}{crl}
u & = & [u_1, u_2] \\
\left \| u \right \| & = & \sqrt{ {u_1}^2 + {u_2}^2 }\\
(\left \| u \right \|)^2 & = & {u_1}^2 + {u_2}^2 \\
\end{array}
</math>
as the Pythagorean theorem, the norm is then the geometric length of its arrow.
Property
Since it plays the role of length, it should satisfy the following norm properties:
- Property N1: <math>\left \| v \right \|</math> is a non-negative real number.
- Property N2: <math>\left \| v \right \|</math> is zero if and only if v is a zero vector.
- Property N3: for any scalar <math>\alpha, \left \| \alpha.v \right \| = |\alpha | \left \| v \right \|</math>
- Property N4: <math>\left \| u + v \right \| = \left \| u \right \| + \left \| v \right \|</math> (triangle inequality).