Let \(A\) be an \(m \times n\) matrix of rank \(r > 0\) and let \(U\) be an echelon form of \(A\). Explain why there exists an invertible matrix \(E\) such that \(A = EU\), and use this factorization to write \(A\) as the sum of \(r\) rank 1 matrices. [Hint: See Theorem 10 in Section 2.4.]

Short Answer

Expert verified

There exists an invertible matrix such that \(A = EU\).

Step by step solution

01

State the column-row expansion of \(AB\)

Theorem 10 states that if \(A\) is \(m \times n\) and \(B\) is \(n \times p\), then

\(\begin{array}{c}AB = \left[ {\begin{array}{*{20}{c}}{{{{\mathop{\rm col}\nolimits} }_1}\left( A \right)}&{{{{\mathop{\rm col}\nolimits} }_2}\left( A \right)}& \cdots &{{{{\mathop{\rm col}\nolimits} }_n}\left( A \right)}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{{{\mathop{\rm row}\nolimits} }_1}\left( B \right)}\\{{{{\mathop{\rm row}\nolimits} }_2}\left( B \right)}\\ \vdots \\{{{{\mathop{\rm row}\nolimits} }_n}\left( B \right)}\end{array}} \right]\\ = {{\mathop{\rm col}\nolimits} _1}\left( A \right){{\mathop{\rm row}\nolimits} _1}\left( B \right) + \cdots + {{\mathop{\rm col}\nolimits} _n}\left( A \right){{\mathop{\rm row}\nolimits} _n}\left( B \right).\end{array}\)

02

Explain the existence of an invertible matrix \(E\)

Consider \(A\) is an \(m \times n\) matrix with rank \(r > 0\), and \(U\) is an echelon form of \(A\). Since \(A\) can be reduced to \(U\) by row operations, there exist invertible elementary matrices \({E_1},...,{E_p}\) with \(A = U\) because the product of invertible matrices is invertible. Therefore, \(A = {\left( {{E_p},...,{E_1}} \right)^{ - 1}}U\).

Consider \(E = {\left( {{E_p},...,{E_1}} \right)^{ - 1}}\), then \(A = EU\).

Let \({c_1},...,{c_n}\) represent the column of \(E\). \(U\) has \({\mathop{\rm r}\nolimits} \) non-zero rows that can be represented as \({\mathop{\rm d}\nolimits} _1^T,...,{\mathop{\rm d}\nolimits} _r^T\) because the rank of \(A\) is \({\mathop{\rm r}\nolimits} \) (according to theorem 10).

\(\begin{aligned} A &= EU\\ &= \left[ {\begin{array}{*{20}{c}}{{c_1}}& \cdots &{{c_m}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{\mathop{\rm d}\nolimits} _1^T}\\ \vdots \\{{\mathop{\rm d}\nolimits} _r^T}\\0\\ \vdots \\0\end{array}} \right]\\ &= {c_1}{\mathop{\rm d}\nolimits} _1^T + \cdots + {c_r}{\mathop{\rm d}\nolimits} _r^T\end{aligned}\)

The sum of the \(r\) rank-1 matrices is \(A = {c_1}{\mathop{\rm d}\nolimits} _1^T + \cdots + {c_r}{\mathop{\rm d}\nolimits} _r^T\).

Thus, there exists an invertible matrix such that \(A = EU\).

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Most popular questions from this chapter

In Exercise 17, Ais an \(m \times n\] matrix. Mark each statement True or False. Justify each answer.

17. a. The row space of A is the same as the column space of \({A^T}\].

b. If B is any echelon form of A, and if B has three nonzero rows, then the first three rows of A form a basis for Row A.

c. The dimensions of the row space and the column space of A are the same, even if Ais not square.

d. The sum of the dimensions of the row space and the null space of A equals the number of rows in A.

e. On a computer, row operations can change the apparent rank of a matrix.

If A is a \({\bf{4}} \times {\bf{3}}\) matrix, what is the largest possible dimension of the row space of A? If Ais a \({\bf{3}} \times {\bf{4}}\) matrix, what is the largest possible dimension of the row space of A? Explain.

Consider the polynomials \({{\bf{p}}_{\bf{1}}}\left( t \right) = {\bf{1}} + t\), \({{\bf{p}}_{\bf{2}}}\left( t \right) = {\bf{1}} - t\), \({{\bf{p}}_{\bf{3}}}\left( t \right) = {\bf{4}}\), \({{\bf{p}}_{\bf{4}}}\left( t \right) = {\bf{1}} + {t^{\bf{2}}}\), and \({{\bf{p}}_{\bf{5}}}\left( t \right) = {\bf{1}} + {\bf{2}}t + {t^{\bf{2}}}\), and let H be the subspace of \({P_{\bf{5}}}\) spanned by the set \(S = \left\{ {{{\bf{p}}_{\bf{1}}},\,{{\bf{p}}_{\bf{2}}},\;{{\bf{p}}_{\bf{3}}},\,{{\bf{p}}_{\bf{4}}},\,{{\bf{p}}_{\bf{5}}}} \right\}\). Use the method described in the proof of the Spanning Set Theorem (Section 4.3) to produce a basis for H. (Explain how to select appropriate members of S.)

Question 11: Let \(S\) be a finite minimal spanning set of a vector space \(V\). That is, \(S\) has the property that if a vector is removed from \(S\), then the new set will no longer span \(V\). Prove that \(S\) must be a basis for \(V\).

Suppose a nonhomogeneous system of six linear equations in eight unknowns has a solution, with two free variables. Is it possible to change some constants on the equations’ right sides to make the new system inconsistent? Explain.

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