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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

Use Exercise 28 to explain why the equation\(Ax = b\)has a solution for all\({\rm{b}}\)in\({\mathbb{R}^m}\)if and only if the equation\({A^T}x = 0\)has only the trivial solution.

Question: Exercises 12-17 develop properties of rank that are sometimes needed in applications. Assume the matrix \(A\) is \(m \times n\).

17. A submatrix of a matrix A is any matrix that results from deleting some (or no) rows and/or columns of A. It can be shown that A has rank \(r\) if and only if A contains an invertible \(r \times r\) submatrix and no longer square submatrix is invertible. Demonstrate part of this statement by explaining (a) why an \(m \times n\) matrix A of rank \(r\) has an \(m \times r\) submatrix \({A_1}\) of rank \(r\), and (b) why \({A_1}\) has an invertible \(r \times r\) submatrix \({A_2}\).

The concept of rank plays an important role in the design of engineering control systems, such as the space shuttle system mentioned in this chapter’s introductory example. A state-space model of a control system includes a difference equation of the form

\({{\mathop{\rm x}\nolimits} _{k + 1}} = A{{\mathop{\rm x}\nolimits} _k} + B{{\mathop{\rm u}\nolimits} _k}\)for \(k = 0,1,....\) (1)

Where \(A\) is \(n \times n\), \(B\) is \(n \times m\), \(\left\{ {{{\mathop{\rm x}\nolimits} _k}} \right\}\) is a sequence of “state vectors” in \({\mathbb{R}^n}\) that describe the state of the system at discrete times, and \(\left\{ {{{\mathop{\rm u}\nolimits} _k}} \right\}\) is a control, or input, sequence. The pair \(\left( {A,B} \right)\) is said to be controllable if

\({\mathop{\rm rank}\nolimits} \left( {\begin{array}{*{20}{c}}B&{AB}&{{A^2}B}& \cdots &{{A^{n - 1}}B}\end{array}} \right) = n\) (2)

The matrix that appears in (2) is called the controllability matrix for the system. If \(\left( {A,B} \right)\) is controllable, then the system can be controlled, or driven from the state 0 to any specified state \({\mathop{\rm v}\nolimits} \) (in \({\mathbb{R}^n}\)) in at most \(n\) steps, simply by choosing an appropriate control sequence in \({\mathbb{R}^m}\). This fact is illustrated in Exercise 18 for \(n = 4\) and \(m = 2\). For a further discussion of controllability, see this text’s website (Case study for Chapter 4).

(M) Show that \(\left\{ {t,sin\,t,cos\,{\bf{2}}t,sin\,t\,cos\,t} \right\}\) is a linearly independent set of functions defined on \(\mathbb{R}\). Start by assuming that

\({c_{\bf{1}}} \cdot t + {c_{\bf{2}}} \cdot sin\,t + {c_{\bf{3}}} \cdot cos\,{\bf{2}}t + {c_{\bf{4}}} \cdot sin\,t\,cos\,t = {\bf{0}}\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\left( {\bf{5}} \right)\)

Equation (5) must hold for all real t, so choose several specific values of t (say, \(t = {\bf{0}},\,.{\bf{1}},\,.{\bf{2}}\)) until you get a system of enough equations to determine that the \({c_j}\) must be zero.

Find a basis for the set of vectors in\({\mathbb{R}^{\bf{3}}}\)in the plane\(x + {\bf{2}}y + z = {\bf{0}}\). (Hint:Think of the equation as a “system” of homogeneous equations.)

Question: Exercises 12-17 develop properties of rank that are sometimes needed in applications. Assume the matrix \(A\) is \(m \times n\).

13. Show that if \(P\) is an invertible \(m \times m\) matrix, then rank\(PA\)=rank\(A\).(Hint: Apply Exercise12 to \(PA\) and \({P^{ - 1}}\left( {PA} \right)\).)

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