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Mention the relevance to the Weierstrass M-test.
 
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== Distinctions ==
== Distinctions ==
Normal convergence implies, but should not be confused with, [[uniform absolute convergence]], i.e. uniform convergence of the series of nonnegative functions <math>\sum_{n=0}^\infty |f_n(x)|</math>. To illustrate this, consider
Normal convergence implies [[uniform absolute convergence]], i.e., uniform convergence of the series of nonnegative functions <math>\sum_{n=0}^\infty |f_n(x)|</math>; this fact is essentially the [[Weierstrass M-test]]. However, they should not be confused; to illustrate this, consider


: <math>f_n(x) = \begin{cases} 1/n, & x = n, \\ 0, & x \ne n. \end{cases}</math>
: <math>f_n(x) = \begin{cases} 1/n, & x = n, \\ 0, & x \ne n. \end{cases}</math>

Latest revision as of 18:20, 5 February 2024

In mathematics normal convergence is a type of convergence for series of functions. Like absolute-convergence, it has the useful property that it is preserved when the order of summation is changed.

History

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The concept of normal convergence was first introduced by René Baire in 1908 in his book Leçons sur les théories générales de l'analyse.

Definition

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Given a set S and functions (or to any normed vector space), the series

is called normally convergent if the series of uniform norms of the terms of the series converges,[1] i.e.,

Distinctions

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Normal convergence implies uniform absolute convergence, i.e., uniform convergence of the series of nonnegative functions ; this fact is essentially the Weierstrass M-test. However, they should not be confused; to illustrate this, consider

Then the series is uniformly convergent (for any ε take n ≥ 1/ε), but the series of uniform norms is the harmonic series and thus diverges. An example using continuous functions can be made by replacing these functions with bump functions of height 1/n and width 1 centered at each natural number n.

As well, normal convergence of a series is different from norm-topology convergence, i.e. convergence of the partial sum sequence in the topology induced by the uniform norm. Normal convergence implies norm-topology convergence if and only if the space of functions under consideration is complete with respect to the uniform norm. (The converse does not hold even for complete function spaces: for example, consider the harmonic series as a sequence of constant functions).

Generalizations

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Local normal convergence

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A series can be called "locally normally convergent on X" if each point x in X has a neighborhood U such that the series of functions ƒn restricted to the domain U

is normally convergent, i.e. such that

where the norm is the supremum over the domain U.

Compact normal convergence

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A series is said to be "normally convergent on compact subsets of X" or "compactly normally convergent on X" if for every compact subset K of X, the series of functions ƒn restricted to K

is normally convergent on K.

Note: if X is locally compact (even in the weakest sense), local normal convergence and compact normal convergence are equivalent.

Properties

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  • Every normal convergent series is uniformly convergent, locally uniformly convergent, and compactly uniformly convergent. This is very important, since it assures that any re-arrangement of the series, any derivatives or integrals of the series, and sums and products with other convergent series will converge to the "correct" value.
  • If is normally convergent to , then any re-arrangement of the sequence (ƒ1, ƒ2, ƒ3 ...) also converges normally to the same ƒ. That is, for every bijection , is normally convergent to .

See also

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References

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  1. ^ Solomentsev, E.D. (2001) [1994], "Normal convergence", Encyclopedia of Mathematics, EMS Press, ISBN 1402006098