# Definition:Invertible Bounded Linear Transformation/Normed Vector Space

## Definition

Let $\struct {V, \norm \cdot_V}$ and $\struct {U, \norm \cdot_U}$ be normed vector spaces.

Let $A : V \to U$ be a bounded linear transformation.

We say that $A$ is **invertible as a bounded linear transformation** if and only if:

- $A$ has an inverse mapping that is a bounded linear transformation.

That is:

- there exists a bounded linear transformation $B : U \to V$ such that:

- $A \circ B = I_U$
- $B \circ A = I_V$

where $I_U$ and $I_V$ are the identity mappings on $U$ and $V$ respectively.

We say that $B$ is the **inverse** of $A$ and write $B = A^{-1}$.

The process of finding an $A^{-1}$ given $A$ is called **inverting**.

## Notes

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Note that a mapping is usually called **invertible** if it has an inverse mapping.

However, in the context of a bounded linear transformation, it often makes sense to insist that this inverse mapping be bounded.

Some sources therefore call a bounded linear transformation $A$ with bounded inverse **invertible**, while simply saying that $A$ **has an inverse** otherwise.

To avoid confusion, on $\mathsf{Pr} \infty \mathsf{fWiki}$ we emphasise that $A$ is **invertible in the sense of a bounded linear transformation** or **invertible as a bounded linear transformation**, if a bounded inverse is insisted.

Where boundedness of the inverse is not required, we can simply call $A$ **invertible**, **invertible as a mapping** or **invertible in the sense of a mapping**.