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I'm reading Luenberger's Optimization by Vector Space Methods which has the following definition:

A finite set $S$ of linearly independent vectors is said to be a basis for the space $X$ if $S$ generates $X$. A vector space having a finite basis is said to be finite dimensional. All other vector spaces are said to be infinite dimensional.

Am I going crazy for thinking that this definition does not really allow for infinite dimensional spaces since $S$ is defined as a finite set? Maybe there's some subtlety I'm missing here?

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  • $\begingroup$ I don't know weher you confuse. Do you know definition of vector space? $\endgroup$
    – Nakayama
    Feb 4 at 15:25
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    $\begingroup$ It is poorly worded. You could save the definition by just omitting the first instance of the word "finite." $\endgroup$
    – Alex Ortiz
    Feb 4 at 15:31
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    $\begingroup$ @AlexOrtiz exactly $\endgroup$ Feb 4 at 15:40

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That definition makes sense. Take, for instance, the vector space $\Bbb R^{\Bbb N}$ of all sequences of real numbers. There is no finite set $S\subset\Bbb R^{\Bbb N}$ which spans $\Bbb R^{\Bbb N}$. Therefore, $\Bbb R^{\Bbb N}$ is infinite-dimensional.

There is a problem with that definition however: it doesn't allow the existence of bases of infinite-dimensional vector spaces.

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  • $\begingroup$ Thank you for confirming. This is what I got hung up on (not allowing bases to exist for infinite dimensional vector spaces). $\endgroup$ Feb 4 at 15:39
  • $\begingroup$ I'm glad I could help. $\endgroup$ Feb 4 at 15:40
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The definition is: $X$ is infinite dimensional iff there does not exist any finite subset $S\subseteq X$ such that $S$ is a basis for $X$.

For instance $X = {\Bbb R}^{\Bbb N}$ (the vector space of all real sequences) is infinite dimensional because whatever finite subset $S \subset X$ you pick, it isn’t a basis for $X$.

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