In mathematical analysis, the uniform norm (or sup norm) assigns to real- or complex-valued bounded functions f defined on a set S the non-negative number
This norm is also called the supremum norm, the Chebyshev norm, or the infinity norm. The name "uniform norm" derives from the fact that a sequence of functions converges to f under the metric derived from the uniform norm if and only if converges to uniformly.
If we allow unbounded functions, this formula does not yield a norm or metric in a strict sense, although the obtained so-called extended metric still allows one to define a topology on the function space in question.
If f is a continuous function on a closed interval, or more generally a compact set, then it is bounded and the supremum in the above definition is attained by the Weierstrass extreme value theorem, so we can replace the supremum by the maximum. In this case, the norm is also called the maximum norm. In particular, for the case of a vector in finite dimensional coordinate space, it takes the form
The reason for the subscript "∞" is that whenever f is continuous
where
where D is the domain of f (and the integral amounts to a sum if D is a discrete set).
The binary function
is then a metric on the space of all bounded functions (and, obviously, any of its subsets) on a particular domain. A sequence { fn : n = 1, 2, 3, ... } converges uniformly to a function f if and only if
We can define closed sets and closures of sets with respect to this metric topology; closed sets in the uniform norm are sometimes called uniformly closed and closures uniform closures. The uniform closure of a set of functions A is the space of all functions that can be approximated by a sequence of uniformly-converging functions on A. For instance, one restatement of the Stone–Weierstrass theorem is that the set of all continuous functions on is the uniform closure of the set of polynomials on .
For complex continuous functions over a compact space, this turns it into a C* algebra.
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