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In Exercises 1–9, assume that the matrices are partitioned conformably for block multiplication. In Exercises 5–8, find formulas for X, Y, and Zin terms of A, B, and C, and justify your calculations. In some cases, you may need to make assumptions about the size of a matrix in order to produce a formula. [Hint:Compute the product on the left, and set it equal to the right side.]

6. \[\left[ {\begin{array}{*{20}{c}}X&{\bf{0}}\\Y&Z\end{array}} \right]\left[ {\begin{array}{*{20}{c}}A&{\bf{0}}\\B&C\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&{\bf{0}}\\{\bf{0}}&I\end{array}} \right]\]

Short Answer

Expert verified

The formulas are \(X = {A^{ - 1}}\), \(Y = - {C^{ - 1}}B{A^{ - 1}}\), and \[Z = {C^{ - 1}}\].

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 shown below:

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

02

Obtain the product

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

\[\begin{array}{c}\left[ {\begin{array}{*{20}{c}}X&0\\Y&Z\end{array}} \right]\left[ {\begin{array}{*{20}{c}}A&0\\B&C\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{X\left( A \right) + 0\left( B \right)}&{X\left( 0 \right) + 0\left( C \right)}\\{Y\left( A \right) + Z\left( B \right)}&{Y\left( 0 \right) + Z\left( C \right)}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{XA + 0 \cdot B}&{X \cdot 0 + 0 \cdot C}\\{YA + ZB}&{Y \cdot 0 + ZC}\end{array}} \right]\end{array}\]

Use the matrix properties\(A \cdot I = A\)and\(A \cdot 0 = 0\).

\[\left[ {\begin{array}{*{20}{c}}X&0\\Y&Z\end{array}} \right]\left[ {\begin{array}{*{20}{c}}A&0\\B&C\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{XA}&0\\{YA + ZB}&{ZC}\end{array}} \right]\]

Thus, \[\left[ {\begin{array}{*{20}{c}}X&0\\Y&Z\end{array}} \right]\left[ {\begin{array}{*{20}{c}}A&0\\B&C\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{XA}&0\\{YA + ZB}&{ZC}\end{array}} \right]\].

03

Equate both the sides

Equate both the matrices as shown below:

\[\left[ {\begin{array}{*{20}{c}}{XA}&0\\{YA + ZB}&{ZC}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&0\\0&I\end{array}} \right]\]

By comparing, the formulas become

\(\begin{array}{c}XA = I\\X\left( {{A^{ - 1}}A} \right) = {A^{ - 1}}\left( I \right)\\X \cdot I = {A^{ - 1}} \cdot I\\X = {A^{ - 1}}\end{array}\)

\[\begin{array}{c}ZC = I\\Z\left( {{C^{ - 1}}C} \right) = {C^{ - 1}}\left( I \right)\\Z \cdot I = {C^{ - 1}} \cdot I\\Z = {C^{ - 1}}\end{array}\]

and

\(\begin{array}{c}YA + ZB = 0\\YA + {C^{ - 1}}B = 0\\YA = - {C^{ - 1}}B.\end{array}\)

Solve further to get

\(\begin{array}{c}\left( {YA} \right){A^{ - 1}} = \left( { - {C^{ - 1}}B} \right){A^{ - 1}}\\Y \cdot \left( {A{A^{ - 1}}} \right) = - {C^{ - 1}}B{A^{ - 1}}\\Y \cdot I = - {C^{ - 1}}B{A^{ - 1}}\\Y = - {C^{ - 1}}B{A^{ - 1}}.\end{array}\)

Therefore, the formulas are \(X = {A^{ - 1}}\), \(Y = - {C^{ - 1}}B{A^{ - 1}}\), and \[Z = {C^{ - 1}}\].

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Most popular questions from this chapter

Let \(A = \left( {\begin{aligned}{*{20}{c}}{\bf{2}}&{ - {\bf{3}}}\\{ - {\bf{4}}}&{\bf{6}}\end{aligned}} \right)\) and \(B = \left( {\begin{aligned}{*{20}{c}}{\bf{8}}&{\bf{4}}\\{\bf{5}}&{\bf{5}}\end{aligned}} \right)\) and \(C = \left( {\begin{aligned}{*{20}{c}}{\bf{5}}&{ - {\bf{2}}}\\{\bf{3}}&{\bf{1}}\end{aligned}} \right)\). Verfiy that \(AB = AC\) and yet \(B \ne C\).

Suppose Ais an \(n \times n\) matrix with the property that the equation \[A{\mathop{\rm x}\nolimits} = 0\] has at least one solution for each b in \({\mathbb{R}^n}\). Without using Theorem 5 or 8, explain why each equation Ax = b has in fact exactly one solution.

When a deep space probe launched, corrections may be necessary to place the probe on a precisely calculated trajectory. Radio elementary provides a stream of vectors, \({{\bf{x}}_{\bf{1}}},....,{{\bf{x}}_k}\), giving information at different times about how the probe’s position compares with its planned trajectory. Let \({X_k}\) be the matrix \(\left[ {{x_{\bf{1}}}.....{x_k}} \right]\). The matrix \({G_k} = {X_k}X_k^T\) is computed as the radar data are analyzed. When \({x_{k + {\bf{1}}}}\) arrives, a new \({G_{k + {\bf{1}}}}\) must be computed. Since the data vector arrive at high speed, the computational burden could be serve. But partitioned matrix multiplication helps tremendously. Compute the column-row expansions of \({G_k}\) and \({G_{k + {\bf{1}}}}\) and describe what must be computed in order to update \({G_k}\) to \({G_{k + {\bf{1}}}}\).

A useful way to test new ideas in matrix algebra, or to make conjectures, is to make calculations with matrices selected at random. Checking a property for a few matrices does not prove that the property holds in general, but it makes the property more believable. Also, if the property is actually false, you may discover this when you make a few calculations.

37. Construct a random \({\bf{4}} \times {\bf{4}}\) matrix Aand test whether \(\left( {A + I} \right)\left( {A - I} \right) = {A^2} - I\). The best way to do this is to compute \(\left( {A + I} \right)\left( {A - I} \right) - \left( {{A^2} - I} \right)\) and verify that this difference is the zero matrix. Do this for three random matrices. Then test \(\left( {A + B} \right)\left( {A - B} \right) = {A^2} - {B^{\bf{2}}}\) the same way for three pairs of random \({\bf{4}} \times {\bf{4}}\) matrices. Report your conclusions.

Suppose Aand Bare \(n \times n\), Bis invertible, and ABis invertible. Show that Ais invertible. (Hint: Let C=AB, and solve this equation for A.)

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