2.2 KiB
Metric spaces
Definition 1: a metric space is a pair
(X,d), whereXis a set anddis a metric onX, which is a function onX \times Xsuch that
dis real, finite and nonnegative,\forall x,y \in X: \quad d(x,y) = 0 \iff x = y,\forall x,y \in X: \quad d(x,y) = d(y,x),\forall x,y,z \in X: \quad d(x,y) \leq d(x,z) + d(y,z).
The metric d is also referred to as a distance function. With x,y \in X: d(x,y) the distance from x to y.
Examples of metric spaces
For the Real line \mathbb{R} the usual metric is defined by
d(x,y) = |x - y|,
for all x,y \in \mathbb{R}. Obtaining a metric space (\mathbb{R}, d).
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For the Euclidean space \mathbb{R}^n with n \in \mathbb{N}, the usual metric is defined by
d(x,y) = \sqrt{\sum_{j=1}^n (x(j) - y(j))^2},
for all x,y \in \mathbb{R}^n with x = (x(j)) and y = (y(j)). Obtaining a metric space (\mathbb{R}^n, d).
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Similar examples exist for the complex plane \mathbb{C} and the unitary space \mathbb{C}^n.
For the space C([a,b]) of all real-valued continuous functions on a closed interval [a,b] with a<b \in \mathbb{R} the metric may be defined by
d(x,y) = \max_{t \in [a,b]} |x(t) - y(t)|,
for all x,y \in C([a,b]). Obtaining a metric space (C([a,b]), d).
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Definition 2: let
l^pwithp \geq 1be the set of sequencesx \in l^pof complex numbers with the property that
\sum_{j \in \mathbb{N}} | x(j) |^p \text{ is convergent},for all
x \in l^p.
We have that a metric d for l^p may be defined by
d(x,y) = (\sum_{j \in \mathbb{N}} | x(j) - y(j) |^p)^\frac{1}{p},
for all x,y \in l^p.
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From definition 2 the sequence space l^\infty follows, which is defined as the set of all bounded sequences x \in l^\infty of complex numbers. A metric d of l^\infty may be defined by
d(x,y) = \sup_{j \in \mathbb{N}} | x(j) - y(j) |,
for all x, y \in l^\infty.
??? note "Proof:"
Will be added later.