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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.

6. \(A = \left[ {\begin{array}{*{20}{c}}1&3&4&0\\{ - 3}&{ - 6}&{ - 7}&2\\3&3&0&{ - 4}\\{ - 5}&{ - 3}&2&9\end{array}} \right],{\mathop{\rm b}\nolimits} = \left[ {\begin{array}{*{20}{c}}1\\{ - 2}\\{ - 1}\\2\end{array}} \right]\)

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

Short Answer

Expert verified

\(x = \left( {3, - 2,1,1} \right)\) and \(y = \left[ {\begin{array}{*{20}{c}}1\\1\\{ - 2}\\1\end{array}} \right]\)

Step by step solution

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

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

Here, \[L = \left[ {\begin{array}{*{20}{c}}1&0&0&0\\{ - 3}&1&0&0\\3&{ - 2}&1&0\\{ - 5}&4&{ - 1}&1\end{array}} \right],{\rm{ }}U = \,\left[ {\begin{array}{*{20}{c}}1&3&4&0\\0&3&5&2\\0&0&{ - 2}&0\\0&0&0&1\end{array}} \right],{\rm{ }}b = \left[ {\begin{array}{*{20}{c}}1\\{ - 2}\\{ - 1}\\2\end{array}} \right]\].

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

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

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

At row two, multiply row one by 3 and add it to row two. At row three, multiply row one by 3 and subtract it from row three. At row four, multiply row one by 5 and add it to row four.

\( \sim \left[ {\begin{array}{*{20}{c}}1&0&0&0&1\\0&1&0&0&1\\0&{ - 2}&1&0&{ - 4}\\0&4&{ - 1}&1&7\end{array}} \right]\)

At row three, multiply row two by 2 and add it to row three. At row four, multiply row two by 4 and subtract it from row four.

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

At row four, multiply row three by 1 and add it to row four.

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

The arithmetic values take place only in column five.

Thus, \(y = \left[ {\begin{array}{*{20}{c}}1\\1\\{ - 2}\\1\end{array}} \right]\).

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:

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

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

At row two, multiply row four by 2 and subtract it from row two.

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

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

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

At row two, multiply row three by 5 and subtract it from row two. At row one, multiply row three by 4 and subtract it from row one.

\( \sim \left[ {\begin{array}{*{20}{c}}1&3&0&0&{ - 3}\\0&3&0&0&{ - 6}\\0&0&1&0&1\\0&0&0&1&1\end{array}} \right]\)

At row two, multiply row two by \(\frac{1}{3}\).

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

At row one, multiply row two by 3 and subtract it from row one.

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

Thus, \(x = \left( {3, - 2,1,1} \right)\).

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Most popular questions from this chapter

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.

Suppose P is invertible and \(A = PB{P^{ - 1}}\). Solve for Bin terms of A.

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

a. If \(A = \left[ {\begin{array}{*{20}{c}}{{A_{\bf{1}}}}&{{A_{\bf{2}}}}\end{array}} \right]\) and \(B = \left[ {\begin{array}{*{20}{c}}{{B_{\bf{1}}}}&{{B_{\bf{2}}}}\end{array}} \right]\), with \({A_{\bf{1}}}\) and \({A_{\bf{2}}}\) the same sizes as \({B_{\bf{1}}}\) and \({B_{\bf{2}}}\), respectively then \(A + B = \left[ {\begin{array}{*{20}{c}}{{A_1} + {B_1}}&{{A_{\bf{2}}} + {B_{\bf{2}}}}\end{array}} \right]\).

b. If \(A = \left[ {\begin{array}{*{20}{c}}{{A_{{\bf{11}}}}}&{{A_{{\bf{12}}}}}\\{{A_{{\bf{21}}}}}&{{A_{{\bf{22}}}}}\end{array}} \right]\) and \(B = \left[ {\begin{array}{*{20}{c}}{{B_1}}\\{{B_{\bf{2}}}}\end{array}} \right]\), then the partitions of \(A\) and \(B\) are comfortable for block multiplication.

Suppose Ais an \(m \times n\) matrix and there exist \(n \times m\) matrices C and D such that \(CA = {I_n}\) and \(AD = {I_m}\). Prove that \(m = n\) and \(C = D\). (Hint: Think about the product CAD.)

Suppose \(AD = {I_m}\) (the \(m \times m\) identity matrix). Show that for any b in \({\mathbb{R}^m}\), the equation \(A{\mathop{\rm x}\nolimits} = {\mathop{\rm b}\nolimits} \) has a solution. (Hint: Think about the equation \(AD{\mathop{\rm b}\nolimits} = {\mathop{\rm b}\nolimits} \).) Explain why Acannot have more rows than columns.

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