Chapter 5: Q5.3-24E (page 267)
Question: A is a \({\bf{3}} \times {\bf{3}}\) matrix with two eigenvalues. Each eigenspace is one-dimensional. Is A diagonalizable? Why?
Short Answer
According to diagonalize theorem, A cannot be diagonalizable.
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Chapter 5: Q5.3-24E (page 267)
Question: A is a \({\bf{3}} \times {\bf{3}}\) matrix with two eigenvalues. Each eigenspace is one-dimensional. Is A diagonalizable? Why?
According to diagonalize theorem, A cannot be diagonalizable.
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Consider an invertible n × n matrix A such that the zero state is a stable equilibrium of the dynamical system What can you say about the stability of the systems.
Question: Is \(\lambda = 2\) an eigenvalue of \(\left( {\begin{array}{*{20}{c}}3&2\\3&8\end{array}} \right)\)? Why or why not?
Question: Find the characteristic polynomial and the eigenvalues of the matrices in Exercises 1-8.
4. \(\left[ {\begin{array}{*{20}{c}}5&-3\\-4&3\end{array}} \right]\)
M] In Exercises 19 and 20, find (a) the largest eigenvalue and (b) the eigenvalue closest to zero. In each case, set \[{{\bf{x}}_{\bf{0}}}{\bf{ = }}\left( {{\bf{1,0,0,0}}} \right)\] and carry out approximations until the approximating sequence seems accurate to four decimal places. Include the approximate eigenvector.
19.\[A{\bf{=}}\left[{\begin{array}{*{20}{c}}{{\bf{10}}}&{\bf{7}}&{\bf{8}}&{\bf{7}}\\{\bf{7}}&{\bf{5}}&{\bf{6}}&{\bf{5}}\\{\bf{8}}&{\bf{6}}&{{\bf{10}}}&{\bf{9}}\\{\bf{7}}&{\bf{5}}&{\bf{9}}&{{\bf{10}}}\end{array}} \right]\]
Let\(D = \left\{ {{{\bf{d}}_1},{{\bf{d}}_2}} \right\}\) and \(B = \left\{ {{{\bf{b}}_1},{{\bf{b}}_2}} \right\}\) be bases for vector space \(V\) and \(W\), respectively. Let \(T:V \to W\) be a linear transformation with the property that
\(T\left( {{{\bf{d}}_1}} \right) = 2{{\bf{b}}_1} - 3{{\bf{b}}_2}\), \(T\left( {{{\bf{d}}_2}} \right) = - 4{{\bf{b}}_1} + 5{{\bf{b}}_2}\)
Find the matrix for \(T\) relative to \(D\), and\(B\).
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