Let V be a vector space of dimension n and let A = {v1, ..., vn} be an ordered basisof V . Suppose w1, ..., wn ∈ V and let (a1j , ..., anj )t denote the coordinates of wjwith respect to A. Put C = [aij ]. Then show that w1, ..., wn is a basis of V if andonly if C is invertible
Question
Let V be a vector space of dimension n and let A = {v1, ..., vn} be an ordered basisof V . Suppose w1, ..., wn ∈ V and let (a1j , ..., anj )t denote the coordinates of wjwith respect to A. Put C = [aij ]. Then show that w1, ..., wn is a basis of V if andonly if C is invertible
Solution
To prove this, we need to show two directions:
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If {w1, ..., wn} is a basis of V, then C is invertible.
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If C is invertible, then {w1, ..., wn} is a basis of V.
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Suppose {w1, ..., wn} is a basis of V. This means that any vector v in V can be expressed as a unique linear combination of the vectors in the basis. In terms of the matrix C, this means that for any vector v in V, there exists a unique solution to the equation Cv = b, where b is the coordinate vector of v with respect to the basis {w1, ..., wn}. This implies that the matrix C is invertible.
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Now suppose that C is invertible. This means that for any vector b in R^n, the equation Cv = b has a unique solution. In terms of the vectors in V, this means that any vector v in V can be expressed as a unique linear combination of the vectors w1, ..., wn. Therefore, {w1, ..., wn} is a basis of V.
Hence, we have shown that {w1, ..., wn} is a basis of V if and only if C is invertible.
Similar Questions
Let T be a linear transformation from an n dimensional vector space V to an mdimensional vector space W and let C be the matrix of T with respect to a basis Aof V and B of W . Show that(a) rank(T ) = rank(C);
(b) Assume that {v1, v2, · · · , vk} is a basis of Y . Show that the linear transform T : X → Y from (a) is invertible. (Hint: Use (a) to define a suitable linear transform U : Y → X and show that it is the inverse of T .)
We proved a theorem stating that for a linear mapping α : U → V , we havedim Kerα + dim Imα = dimU.A part of the proof went as follows. Assuming dim Kerα = m, there is a basis of Kerα consisting ofm vectors; denote them by u1, . . . , um. Since dim Imα = n, there is a basis of Imα consisting of nvectors; denote them by v1, . . . , vn. Since v1 is in Imα, there is w1 ∈ U such that α(w1) = v1, andsimilarly for all other vectors in the set v1, . . . , vn; in this way, we define n vectors w1, . . . , wn.Now consider a vector u ∈ U . Since α(u) is in Imα, we have α(u) = d1v1 + · · · + dnvn for somenumbers d1, . . . , dn. Consider a vector u′ ∈ U defined as u′ = d1w1 + · · · + dnwn.Prove that u − u′ ∈ Kerα.
We proved a theorem stating that for a linear mapping α : U → V , we havedim Kerα + dim Imα = dimU.A part of the proof went as follows. Assuming dim Kerα = m, there is a basis of Kerα consisting ofm vectors; denote them by u1, . . . , um. Since dim Imα = n, there is a basis of Imα consisting of nvectors; denote them by v1, . . . , vn. Since v1 is in Imα, there is w1 ∈ U such that α(w1) = v1, andsimilarly for all other vectors in the set v1, . . . , vn; in this way, we define n vectors w1, . . . , wn.Now consider a vector u ∈ U . Since α(u) is in Imα, we have α(u) = d1v1 + · · · + dnvn for somenumbers d1, . . . , dn. Consider a vector u′ ∈ U defined as u′ = d1w1 + · · · + dnwn.Continuing this proof, prove that (u − u′) ∈ Kerα.
. If is invertible then is invertible.
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