The Matrix of A Linear Transformation
Now suppose T : V → W is a linear transformation, {α1, ..., αn} is a basis for V and {β1, ..., βm} is a basis for W. Let φ and ψ be the coordinate isomorphisms for V and W, respectively, relative to the given bases. Then the map T1 = ψ-1 o T o φ is a linear transformation from Rn to Rm, and therefore has a matrix t; its j-th column is ψ-1(T(αj)) for j = 1, ..., n. This matrix is called the matrix of T with respect to the ordered bases {α1, ..., αn} and {β1, ..., βm}. If η = T(ξ) and y and x are the coordinate tuples of η and ξ, then y = ψ-1(T(φ(x))) = tx. Conversely, if ξ is in V and x = φ-1(ξ) is the coordinate tuple of ξ with respect to {α1, ..., αn}, and we set y = tx and η = ψ(y), then η = ψ(T1(x)) = T(ξ). That is, if ξ is in V and η is in W and x and y are their coordinate tuples, then y = tx if and only if η = T(ξ).
Theorem Suppose U, V and W are vector spaces of finite dimension and an ordered basis is chosen for each. If T : U → V and S : V → W are linear transformations with matrices s and t, then the matrix of the linear transformation S o T : U → W (with respect to the given bases) is st.
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“In all cultures, the family imprints its members with selfhood. Human experience of identity has two elements; a sense of belonging and a sense of being separate. The laboratory in which these ingredients are mixed and dispensed is the family, the matrix of identity.”
—Salvador Minuchin (20th century)