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1-6: Solve the equation Ax=b by using the LU factorization given for A. In Exercises 1 and 2, also solve \(Ax = b\) by ordinary row reduction.

4. \(A = \left[ {\begin{array}{*{20}{c}}2&{ - 2}&4\\1&{ - 3}&1\\3&7&5\end{array}} \right],{\mathop{\rm b}\nolimits} = \left[ {\begin{array}{*{20}{c}}0\\{ - 5}\\7\end{array}} \right]\)

\(A = \left[ {\begin{array}{*{20}{c}}1&0&0\\{\frac{1}{2}}&1&0\\{\frac{3}{2}}&{ - 5}&1\end{array}} \right]\,\left[ {\begin{array}{*{20}{c}}2&{ - 2}&4\\0&{ - 2}&{ - 1}\\0&0&{ - 6}\end{array}} \right]\)

Short Answer

Expert verified

\(x = \left( { - 5,1,3} \right)\) and \(y = \left[ {\begin{array}{*{20}{c}}0\\{ - 5}\\{ - 18}\end{array}} \right]\)

Step by step solution

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01

Solve the equation \(Ly = b\) for y

Acan be written in the form \(A = LU\), where Lis an \(m \times m\) lower triangular matrix with 1s on the diagonal, and U is an \(m \times n\) echelon form of A.

When \(A = LU\), the equation \(Ax = b\) can be written as \(L\left( {Ux} \right) = {\mathop{\rm b}\nolimits} \).

Write y for \(Ux\) and find x by solving the pair of equations

\(\begin{array}{l}Ly = b,\\Ux = y.\end{array}\)

It is given that \[L = \left[ {\begin{array}{*{20}{c}}1&0&0\\{\frac{1}{2}}&1&0\\{\frac{3}{2}}&{ - 5}&1\end{array}} \right]\,{\rm{, }}U = \left[ {\begin{array}{*{20}{c}}2&{ - 2}&4\\0&{ - 2}&{ - 1}\\0&0&{ - 6}\end{array}} \right],{\rm{ }}b = \left[ {\begin{array}{*{20}{c}}0\\{ - 5}\\7\end{array}} \right]\].

The matrix \(\left[ {\begin{array}{*{20}{c}}L&b\end{array}} \right]\) is shown below:

\(\left[ {\begin{array}{*{20}{c}}L&b\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}1&0&0&0\\{\frac{1}{2}}&1&0&{ - 5}\\{\frac{3}{2}}&{ - 5}&1&7\end{array}} \right]\)

Perform an elementary row operation to produce the row-echelon form of the matrix.

At row two, multiply row one by \(\frac{1}{2}\) and subtract it from row two. At row three, multiply row one by \(\frac{1}{2}\) and subtract it from row three.

\( \sim \left[ {\begin{array}{*{20}{c}}1&0&0&0\\0&1&0&{ - 5}\\0&{ - 5}&1&7\end{array}} \right]\)

At row three, multiply row two by 5 and add it to row three.

\( \sim \left[ {\begin{array}{*{20}{c}}1&0&0&0\\0&1&0&{ - 5}\\0&0&1&{ - 18}\end{array}} \right]\)

The arithmetic values take place only in column four.

Thus, \(y = \left[ {\begin{array}{*{20}{c}}0\\{ - 5}\\{ - 18}\end{array}} \right]\).

02

Use back-substitution to solve the equation \(Ux = y\) for x

The matrix \(\left[ {\begin{array}{*{20}{c}}U&y\end{array}} \right]\) is shown below:

\(\left[ {\begin{array}{*{20}{c}}U&y\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}2&{ - 2}&4&0\\0&{ - 2}&{ - 1}&{ - 5}\\0&0&{ - 6}&{ - 18}\end{array}} \right]\)

Perform an elementary row operation to produce the row-echelon form of the matrix.

At row three, multiply row three by \( - \frac{1}{6}\).

\[ \sim \left[ {\begin{array}{*{20}{c}}2&{ - 2}&4&0\\0&{ - 2}&{ - 1}&{ - 5}\\0&0&1&3\end{array}} \right]\]

At row two, multiply row three by \(1\) and add it to row two. At row one, multiply row three by 4 and subtract it from row one.

\[ \sim \left[ {\begin{array}{*{20}{c}}2&{ - 2}&0&{ - 12}\\0&{ - 2}&0&{ - 2}\\0&0&1&3\end{array}} \right]\]

At row two, multiply row two by \( - \frac{1}{2}\).

\[ \sim \left[ {\begin{array}{*{20}{c}}2&{ - 2}&0&{ - 12}\\0&1&0&1\\0&0&1&3\end{array}} \right]\]

At row one, multiply row two by \(2\) and add it to row one.

\[ \sim \left[ {\begin{array}{*{20}{c}}2&0&0&{ - 10}\\0&1&0&1\\0&0&1&3\end{array}} \right]\]

At row one, multiply row one by \(\frac{1}{2}\).

\[ \sim \left[ {\begin{array}{*{20}{c}}1&0&0&{ - 5}\\0&1&0&1\\0&0&1&3\end{array}} \right]\]

Thus, \(x = \left( { - 5,1,3} \right)\).

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Most popular questions from this chapter

In exercises 11 and 12, mark each statement True or False. Justify each answer.

a. The definition of the matrix-vector product \(A{\bf{x}}\) is a special case of block multiplication.

b. If \({A_{\bf{1}}}\), \({A_{\bf{2}}}\), \({B_{\bf{1}}}\), and \({B_{\bf{2}}}\) are \(n \times n\) matrices, \[A = \left[ {\begin{array}{*{20}{c}}{{A_{\bf{1}}}}\\{{A_{\bf{2}}}}\end{array}} \right]\] and \(B = \left[ {\begin{array}{*{20}{c}}{{B_{\bf{1}}}}&{{B_{\bf{2}}}}\end{array}} \right]\), then the product \(BA\) is defined, but \(AB\) is not.

Suppose the transfer function W(s) in Exercise 19 is invertible for some s. It can be showed that the inverse transfer function \(W{\left( s \right)^{ - {\bf{1}}}}\), which transforms outputs into inputs, is the Schur complement of \(A - BC - s{I_n}\) for the matrix below. Find the Sachur complement. See Exercise 15.

\(\left[ {\begin{array}{*{20}{c}}{A - BC - s{I_n}}&B\\{ - C}&{{I_m}}\end{array}} \right]\)

Suppose \({A_{{\bf{11}}}}\) is invertible. Find \(X\) and \(Y\) such that

\[\left[ {\begin{array}{*{20}{c}}{{A_{{\bf{11}}}}}&{{A_{{\bf{12}}}}}\\{{A_{{\bf{21}}}}}&{{A_{{\bf{22}}}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}I&{\bf{0}}\\X&I\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{A_{{\bf{11}}}}}&{\bf{0}}\\{\bf{0}}&S\end{array}} \right]\left[ {\begin{array}{*{20}{c}}I&Y\\{\bf{0}}&I\end{array}} \right]\]

Where \(S = {A_{{\bf{22}}}} - {A_{21}}A_{{\bf{11}}}^{ - {\bf{1}}}{A_{{\bf{12}}}}\). The matrix \(S\) is called the Schur complement of \({A_{{\bf{11}}}}\). Likewise, if \({A_{{\bf{22}}}}\) is invertible, the matrix \({A_{{\bf{11}}}} - {A_{{\bf{12}}}}A_{{\bf{22}}}^{ - {\bf{1}}}{A_{{\bf{21}}}}\) is called the Schur complement of \({A_{{\bf{22}}}}\). Such expressions occur frequently in the theory of systems engineering, and elsewhere.

Exercises 15 and 16 concern arbitrary matrices A, B, and Cfor which the indicated sums and products are defined. Mark each statement True or False. Justify each answer.

15. a. If A and B are \({\bf{2}} \times {\bf{2}}\) with columns \({{\bf{a}}_1},{{\bf{a}}_2}\) and \({{\bf{b}}_1},{{\bf{b}}_2}\) respectively, then \(AB = \left( {\begin{aligned}{*{20}{c}}{{{\bf{a}}_1}{{\bf{b}}_1}}&{{{\bf{a}}_2}{{\bf{b}}_2}}\end{aligned}} \right)\).

b. Each column of ABis a linear combination of the columns of Busing weights from the corresponding column of A.

c. \(AB + AC = A\left( {B + C} \right)\)

d. \({A^T} + {B^T} = {\left( {A + B} \right)^T}\)

e. The transpose of a product of matrices equals the product of their transposes in the same order.

In Exercises 1โ€“9, assume that the matrices are partitioned conformably for block multiplication. In Exercises 5โ€“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.]

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

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