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In the finite-dimensional case, the second condition above is implied by the first.
The statement is essentially the same as the finite-dimensional version.
Let A be an operator on a finite-dimensional inner product space.
In this case, B will be a finite-dimensional, real algebra.
When the vector space is not finite-dimensional, further distinctions are needed.
In the finite-dimensional case, there is a somewhat more explicit formulation.
This finite-dimensional problem is then implemented on a computer.
In particular, if either of or is finite-dimensional, these maps are isomorphisms.
In the case of finite-dimensional spaces, both theories perfectly match.
For simplicity, it will be assumed that all objects in the article are finite-dimensional.
Finite-dimensional division algebras over the real numbers are also very rare.
Let V be a finite-dimensional vector space over a field k.
All of these are again finite-dimensional vector spaces over k.
A vector space that has a finite basis is called finite-dimensional.
In fact, there are stronger statements than the absence of finite-dimensional representations.
For simplicity, the following assumes all relevant state spaces are finite-dimensional.
Note that a space is, by this definition, finite-dimensional.
Each module in a category O has finite-dimensional weight spaces.
This is true regardless of whether H is finite-dimensional or not.
Consider linear operators on a finite-dimensional vector space over a perfect field.
Jordan canonical form, where the finite-dimensional case is discussed in some detail.
If the vector space is a finite-dimensional real or complex one, all norms are equivalent.
They arise, for example, in the study of finite-dimensional modules over an algebra.
The most important distinction is between finite-dimensional representations and infinite-dimensional ones.
Additional algebraic structures can also be imposed in the finite-dimensional case.