Definition of pre-image of linear transformation

Created almost 9 years ago, updated about 8 hours ago

Definition: The pre-image of a subset \(B \subseteq W\) under a linear transformation \(T: V \to W\) is:
\[T^{-1}(B) = \{\mathbf{v} \in V : T(\mathbf{v}) \in B\}\]

When \(B = \{\mathbf{w}\}\) is a single vector, the pre-image is:
\[T^{-1}(\mathbf{w}) = \{\mathbf{v} \in V : T(\mathbf{v}) = \mathbf{w}\}\]

Key property: If \(B\) is a subspace of \(W\), then \(T^{-1}(B)\) is a subspace of \(V\).

Key property: If \(T(\mathbf{v}_p) = \mathbf{w}\) for some particular \(\mathbf{v}_p\), then:
\[T^{-1}(\mathbf{w}) = \mathbf{v}_p + \ker(T)\]
The pre-image is a coset (translate) of the kernel.

Like how this is organised?

Build your own knowledge tree on knowen.md: notes, decisions and tasks in one connected markdown graph, shared with your team and your AI agents.