A normed vector space is a vector space equipped with a function
norm: V => F. The main constraint is that the norm of a vector must be
scaled linearly when the vector is scaled; that is
norm(k *: v) == k.abs * norm(v). Additionally, a normed vector space is
also a MetricSpace, where distance(v, w) = norm(v - w), and so must
obey the triangle inequality.
An example of a normed vector space is R^n equipped with the euclidean
vector length as the norm.
A normed vector space is a vector space equipped with a function
norm: V => F
. The main constraint is that the norm of a vector must be scaled linearly when the vector is scaled; that isnorm(k *: v) == k.abs * norm(v)
. Additionally, a normed vector space is also aMetricSpace
, wheredistance(v, w) = norm(v - w)
, and so must obey the triangle inequality.An example of a normed vector space is R^n equipped with the euclidean vector length as the norm.