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Linear Algebra and its Applications
Found in: Page 267
Linear Algebra and its Applications

Linear Algebra and its Applications

Book edition 5th
Author(s) David C. Lay, Steven R. Lay and Judi J. McDonald
Pages 483 pages
ISBN 978-03219822384

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Short Answer

Use Exercise 12 to find the eigenvalues of the matrices in Exercises 13 and 14.

14. \(A{\bf{ = }}\left( {\begin{array}{*{20}{c}}{\bf{1}}&{\bf{5}}&{{\bf{ - 6}}}&{{\bf{ - 7}}}\\{\bf{2}}&{\bf{4}}&{\bf{5}}&{\bf{2}}\\{\bf{0}}&{\bf{0}}&{{\bf{ - 7}}}&{{\bf{ - 4}}}\\{\bf{0}}&{\bf{0}}&{\bf{3}}&{\bf{1}}\end{array}} \right)\)

The eigenvalues of \(A\) are \( - 1\), \( - 1\), \( - 5\), \(6\).

See the step by step solution

Step by Step Solution

Step 1: Find the characteristic polynomial of \(U\)

Assume \(G = \left( {\begin{array}{*{20}{c}}U&X\\0&V\end{array}} \right)\).

Then we have,

\(\begin{aligned}{c}A &= \left( {\begin{aligned}{*{20}{c}}1&5&{ - 6}&{ - 7}\\2&4&5&2\\0&0&{ - 7}&{ - 4}\\0&0&3&1\end{aligned}} \right)\\ &= \left( {\begin{aligned}{*{20}{c}}U&X\\0&V\end{aligned}} \right)\end{aligned}\)

On comparison we get,

\(U = \left( {\begin{aligned}{*{20}{c}}1&5\\2&4\end{aligned}} \right)\), \(V = \left( {\begin{aligned}{*{20}{c}}{ - 7}&{ - 4}\\3&1\end{aligned}} \right)\)

Now characteristic polynomial of \(U\) are as shown below:

\(\begin{aligned}{c}\det \left( {\begin{aligned}{*{20}{c}}{1 - \lambda }&5\\2&{4 - \lambda }\end{aligned}} \right) &= \left( {1 - \lambda } \right)\left( {4 - \lambda } \right) - 10\\ &= {\lambda ^2} - 5\lambda - 6\\ &= \left( {\lambda + 1} \right)\left( {\lambda - 6} \right)\end{aligned}\)

Step 2: Find the characteristic polynomial of \(V\)

\(\begin{aligned}{c}\det \left( {\begin{aligned}{*{20}{c}}{ - 7 - \lambda }&{ - 4}\\3&{1 - \lambda }\end{aligned}} \right) &= \left( { - 7 - \lambda } \right)\left( {1 - \lambda } \right) + 12\\ &= {\lambda ^2} + 6\lambda + 5\\ &= \left( {\lambda + 1} \right)\left( {\lambda + 5} \right)\end{aligned}\)

On multiplication we get the characteristic polynomial of \(A\).

\(\begin{aligned}{c}A &= \left( {\lambda + 1} \right)\left( {\lambda - 6} \right)\left( {\lambda + 1} \right)\left( {\lambda + 5} \right)\\ &= {\left( {\lambda + 1} \right)^2}\left( {\lambda + 5} \right)\left( {\lambda - 6} \right)\end{aligned}\)

Thus, the eigenvalues of \(A\) are \( - 1\), \( - 1\), \( - 5\), \(6\).

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