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Suppose \({A_{{\bf{11}}}}\) is an invertible matrix. Find matrices Xand Ysuch that the product below has the form indicated. Also,compute \({B_{{\bf{22}}}}\). [Hint:Compute the product on the left, and setit equal to the right side.]

\[\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\X&I&{\bf{0}}\\Y&{\bf{0}}&I\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{A_{{\bf{1}}1}}}&{{A_{{\bf{1}}2}}}\\{{A_{{\bf{2}}1}}}&{{A_{{\bf{2}}2}}}\\{{A_{{\bf{3}}1}}}&{{A_{{\bf{3}}2}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\{\bf{0}}&{{B_{22}}}\\{\bf{0}}&{{B_{32}}}\end{array}} \right]\]

Short Answer

Expert verified

The matrices are \[X = - {A_{11}}^{ - 1}{A_{21}}\] and \[Y = - {A_{11}}^{ - 1}{A_{31}}\]. Also, \[{B_{22}} = {A_{22}} - {A_{21}}{A_{11}}^{ - 1}{A_{12}}\].

Step by step solution

01

State the row-column rule

If the sum of the products of matching entries from row\(i\)of matrix A and column\(j\)of matrix B equals the item in row\(i\)and column\(j\)of AB, then it can be said that product AB is defined.

The product is \({\left( {AB} \right)_{ij}} = {a_{i1}}{b_{1j}} + {a_{i2}}{b_{2j}} + ... + {a_{in}}{b_{nj}}\).

02

Obtain the product

Compute the product of the left part of the given equation by using therow-column rule, as shown below:

\[\begin{array}{l}\left[ {\begin{array}{*{20}{c}}I&0&0\\X&I&0\\Y&0&I\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{A_{11}}}&{{A_{12}}}\\{{A_{21}}}&{{A_{22}}}\\{{A_{31}}}&{{A_{32}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\0&{{B_{22}}}\\0&{{B_{32}}}\end{array}} \right]\\\left[ {\begin{array}{*{20}{c}}{I\left( {{A_{11}}} \right) + 0\left( {{A_{21}}} \right) + 0\left( {{A_{31}}} \right)}&{I\left( {{A_{12}}} \right) + 0\left( {{A_{22}}} \right) + 0\left( {{A_{32}}} \right)}\\{X\left( {{A_{11}}} \right) + I\left( {{A_{21}}} \right) + 0\left( {{A_{31}}} \right)}&{X\left( {{A_{12}}} \right) + I\left( {{A_{22}}} \right) + 0\left( {{A_{32}}} \right)}\\{Y\left( {{A_{11}}} \right) + 0\left( {{A_{21}}} \right) + I\left( {{A_{31}}} \right)}&{Y\left( {{A_{12}}} \right) + 0\left( {{A_{22}}} \right) + I\left( {{A_{32}}} \right)}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\0&{{B_{22}}}\\0&{{B_{32}}}\end{array}} \right]\\\left[ {\begin{array}{*{20}{c}}{{A_{11}}}&{{A_{12}}}\\{X{A_{11}} + {A_{21}}}&{X{A_{12}} + {A_{22}}}\\{Y{A_{11}} + {A_{31}}}&{Y{A_{12}} + {A_{32}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\0&{{B_{22}}}\\0&{{B_{32}}}\end{array}} \right]\end{array}\]

Thus, \[\left[ {\begin{array}{*{20}{c}}{{A_{11}}}&{{A_{12}}}\\{X{A_{11}} + {A_{21}}}&{X{A_{12}} + {A_{22}}}\\{Y{A_{11}} + {A_{31}}}&{Y{A_{12}} + {A_{32}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\0&{{B_{22}}}\\0&{{B_{32}}}\end{array}} \right]\].

03

Equate both the sides

Equate both the matrices, as shown below:

\[\left[ {\begin{array}{*{20}{c}}{{A_{11}}}&{{A_{12}}}\\{X{A_{11}} + {A_{21}}}&{X{A_{12}} + {A_{22}}}\\{Y{A_{11}} + {A_{31}}}&{Y{A_{12}} + {A_{32}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\0&{{B_{22}}}\\0&{{B_{32}}}\end{array}} \right]\]

By comparing, the formulas obtained are shown below:

\[\begin{array}{c}X{A_{11}} + {A_{21}} = 0\\X{A_{11}} = - {A_{21}}\\X\left( {{A_{11}}^{ - 1}{A_{11}}} \right) = - {A_{11}}^{ - 1}{A_{21}}\\X = - {A_{11}}^{ - 1}{A_{21}}\end{array}\]

And,

\[\begin{array}{c}Y{A_{11}} + {A_{31}} = 0\\Y{A_{11}} = - {A_{31}}\\Y\left( {{A_{11}}^{ - 1}{A_{11}}} \right) = - {A_{11}}^{ - 1}{A_{31}}\\Y = - {A_{11}}^{ - 1}{A_{31}}\end{array}\]

Therefore, the formulas are \[X = - {A_{11}}^{ - 1}{A_{21}}\] and \[Y = - {A_{11}}^{ - 1}{A_{31}}\].

By equating the entries, it is also observed that \[X{A_{12}} + {A_{22}} = {B_{22}}\].

\[\begin{array}{l}{B_{22}} = X{A_{12}} + {A_{22}}\\{B_{22}} = - {A_{11}}^{ - 1}{A_{21}}{A_{12}} + {A_{22}}\\{B_{22}} = {A_{22}} - {A_{21}}{A_{11}}^{ - 1}{A_{12}}\end{array}\]

Thus, \[{B_{22}} = {A_{22}} - {A_{21}}{A_{11}}^{ - 1}{A_{12}}\].

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Most popular questions from this chapter

Let \(X\) be \(m \times n\) data matrix such that \({X^T}X\) is invertible., and let \(M = {I_m} - X{\left( {{X^T}X} \right)^{ - {\bf{1}}}}{X^T}\). Add a column \({x_{\bf{0}}}\) to the data and form

\(W = \left[ {\begin{array}{*{20}{c}}X&{{x_{\bf{0}}}}\end{array}} \right]\)

Compute \({W^T}W\). The \(\left( {{\bf{1}},{\bf{1}}} \right)\) entry is \({X^T}X\). Show that the Schur complement (Exercise 15) of \({X^T}X\) can be written in the form \({\bf{x}}_{\bf{0}}^TM{{\bf{x}}_{\bf{0}}}\). It can be shown that the quantity \({\left( {{\bf{x}}_{\bf{0}}^TM{{\bf{x}}_{\bf{0}}}} \right)^{ - {\bf{1}}}}\) is the \(\left( {{\bf{2}},{\bf{2}}} \right)\)-entry in \({\left( {{W^T}W} \right)^{ - {\bf{1}}}}\). This entry has a useful statistical interpretation, under appropriate hypotheses.

In the study of engineering control of physical systems, a standard set of differential equations is transformed by Laplace transforms into the following system of linear equations:

\(\left[ {\begin{array}{*{20}{c}}{A - s{I_n}}&B\\C&{{I_m}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{\bf{x}}\\{\bf{u}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{\bf{0}}\\{\bf{y}}\end{array}} \right]\)

Where \(A\) is \(n \times n\), \(B\) is \(n \times m\), \(C\) is \(m \times n\), and \(s\) is a variable. The vector \({\bf{u}}\) in \({\mathbb{R}^m}\) is the โ€œinputโ€ to the system, \({\bf{y}}\) in \({\mathbb{R}^m}\) is the โ€œoutputโ€ and \({\bf{x}}\) in \({\mathbb{R}^n}\) is the โ€œstateโ€ vector. (Actually, the vectors \({\bf{x}}\), \({\bf{u}}\) and \({\bf{v}}\) are functions of \(s\), but we suppress this fact because it does not affect the algebraic calculations in Exercises 19 and 20.)

Suppose Tand U are linear transformations from \({\mathbb{R}^n}\) to \({\mathbb{R}^n}\) such that \(T\left( {U{\mathop{\rm x}\nolimits} } \right) = {\mathop{\rm x}\nolimits} \) for all x in \({\mathbb{R}^n}\) . Is it true that \(U\left( {T{\mathop{\rm x}\nolimits} } \right) = {\mathop{\rm x}\nolimits} \) for all x in \({\mathbb{R}^n}\)? Why or why not?

Generalize the idea of Exercise 21(a) [not 21(b)] by constructing a \(5 \times 5\) matrix \(M = \left[ {\begin{array}{*{20}{c}}A&0\\C&D\end{array}} \right]\) such that \({M^2} = I\). Make C a nonzero \(2 \times 3\) matrix. Show that your construction works.

In Exercise 10 mark each statement True or False. Justify each answer.

10. a. A product of invertible \(n \times n\) matrices is invertible, and the inverse of the product of their inverses in the same order.

b. If A is invertible, then the inverse of \({A^{ - {\bf{1}}}}\) is A itself.

c. If \(A = \left( {\begin{aligned}{*{20}{c}}a&b\\c&d\end{aligned}} \right)\) and \(ad = bc\), then A is not invertible.

d. If A can be row reduced to the identity matrix, then A must be invertible.

e. If A is invertible, then elementary row operations that reduce A to the identity \({I_n}\) also reduce \({A^{ - {\bf{1}}}}\) to \({I_n}\).

Let \(A = \left( {\begin{aligned}{*{20}{c}}1&1&1\\1&2&3\\1&4&5\end{aligned}} \right)\), and \(D = \left( {\begin{aligned}{*{20}{c}}2&0&0\\0&3&0\\0&0&5\end{aligned}} \right)\). Compute \(AD\) and \(DA\). Explain how the columns or rows of A change when A is multiplied by D on the right or on the left. Find a \(3 \times 3\) matrix B, not the identity matrix or the zero matrix, such that \(AB = BA\).

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