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The inverse of \(\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\C&I&{\bf{0}}\\A&B&I\end{array}} \right]\) is \(\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\Z&I&{\bf{0}}\\X&Y&I\end{array}} \right]\). Find X, Y, and Z.

Short Answer

Expert verified

The values are \(X = BC - A\), \[Y = - B\], and \[Z = - C\].

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

Also, the product of matrix A with its inverse always gives theidentity matrix I.

02

Obtain the product

Compute the product of\(\left[ {\begin{array}{*{20}{c}}I&0&0\\C&I&0\\A&B&I\end{array}} \right]\)with\(\left[ {\begin{array}{*{20}{c}}I&0&0\\Z&I&0\\X&Y&I\end{array}} \right]\) to get theidentity matrix\(\left[ {\begin{array}{*{20}{c}}1&0&0\\0&1&0\\0&0&1\end{array}} \right]\).

\(\begin{array}{c}\left[ {\begin{array}{*{20}{c}}I&0&0\\C&I&0\\A&B&I\end{array}} \right]\left[ {\begin{array}{*{20}{c}}I&0&0\\Z&I&0\\X&Y&I\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&0&0\\0&I&0\\0&0&I\end{array}} \right]\\\left[ {\begin{array}{*{20}{c}}{I\left( I \right) + 0\left( Z \right) + 0\left( X \right)}&{I\left( 0 \right) + 0\left( I \right) + 0\left( Y \right)}&{I\left( 0 \right) + 0\left( 0 \right) + 0\left( I \right)}\\{C\left( I \right) + I\left( Z \right) + 0\left( X \right)}&{C\left( 0 \right) + I\left( I \right) + 0\left( Y \right)}&{C\left( 0 \right) + I\left( 0 \right) + 0\left( I \right)}\\{A\left( I \right) + B\left( Z \right) + I\left( X \right)}&{A\left( 0 \right) + B\left( I \right) + I\left( Y \right)}&{A\left( 0 \right) + B\left( 0 \right) + I\left( I \right)}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&0&0\\0&I&0\\0&0&I\end{array}} \right]\\\left[ {\begin{array}{*{20}{c}}I&0&0\\{C + Z}&I&0\\{A + BZ + X}&{B + Y}&I\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&0&0\\0&I&0\\0&0&I\end{array}} \right]\end{array}\)

Thus, \(\left[ {\begin{array}{*{20}{c}}I&0&0\\{C + Z}&I&0\\{A + BZ + X}&{B + Y}&I\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&0&0\\0&I&0\\0&0&I\end{array}} \right]\).

03

Equate both the sides

Equate both the matrices, as shown below:

\(\left[ {\begin{array}{*{20}{c}}I&0&0\\{C + Z}&I&0\\{A + BZ + X}&{B + Y}&I\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&0&0\\0&I&0\\0&0&I\end{array}} \right]\)

By comparing, the formulas obtained are shown below:

\[\begin{array}{c}C + Z = 0\\Z = - C\end{array}\]

And

\[\begin{array}{c}B + Y = 0\\Y = - B\end{array}\]

And

\(\begin{array}{c}A + BZ + X = 0\\A + B\left( { - C} \right) + X = 0\\A - BC + X = 0\\X = BC - A\end{array}\)

Therefore, the values are \(X = BC - A\), \[Y = - B\], and \[Z = - C\].

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Most popular questions from this chapter

In Exercises 33 and 34, Tis a linear transformation from \({\mathbb{R}^2}\) into \({\mathbb{R}^2}\). Show that T is invertible and find a formula for \({T^{ - 1}}\).

33. \(T\left( {{x_1},{x_2}} \right) = \left( { - 5{x_1} + 9{x_2},4{x_1} - 7{x_2}} \right)\)

Use matrix algebra to show that if A is invertible and D satisfies \(AD = I\) then \(D = {A^{ - {\bf{1}}}}\).

In Exercises 1 and 2, compute each matrix sum or product if it is defined. If an expression is undefined, explain why. Let

\(A = \left( {\begin{aligned}{*{20}{c}}2&0&{ - 1}\\4&{ - 5}&2\end{aligned}} \right)\), \(B = \left( {\begin{aligned}{*{20}{c}}7&{ - 5}&1\\1&{ - 4}&{ - 3}\end{aligned}} \right)\), \(C = \left( {\begin{aligned}{*{20}{c}}1&2\\{ - 2}&1\end{aligned}} \right)\), \(D = \left( {\begin{aligned}{*{20}{c}}3&5\\{ - 1}&4\end{aligned}} \right)\) and \(E = \left( {\begin{aligned}{*{20}{c}}{ - 5}\\3\end{aligned}} \right)\)

\(A + 2B\), \(3C - E\), \(CB\), \(EB\).

Let Abe an invertible \(n \times n\) matrix, and let B be an \(n \times p\) matrix. Show that the equation \(AX = B\) has a unique solution \({A^{ - 1}}B\).

Show that block upper triangular matrix \(A\) in Example 5is invertible if and only if both \({A_{{\bf{11}}}}\) and \({A_{{\bf{12}}}}\) are invertible. [Hint: If \({A_{{\bf{11}}}}\) and \({A_{{\bf{12}}}}\) are invertible, the formula for \({A^{ - {\bf{1}}}}\) given in Example 5 actually works as the inverse of \(A\).] This fact about \(A\) is an important part of several computer algorithims that estimates eigenvalues of matrices. Eigenvalues are discussed in chapter 5.

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