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

a. A set is convex if \({\bf{x}},{\bf{y}} \in S\) implies that the line segment between x and y is contained is S.

b. If S and T are convex sets, then \(S \cap T\) is also convex.

c. If S is a nonempty subset of \({\mathbb{R}^{\bf{5}}}\) and \({\bf{y}} \in {\bf{conv}}\,\,S\), then there exists distinct points \({{\bf{v}}_{\bf{1}}}\),….\({{\bf{v}}_{\bf{6}}}\).

Short Answer

Expert verified

a. The given statement is True.

b. The given statement is True

c. The given statement is True.

Step by step solution

01

Check for statement (a)

Using the definition of convex, a set S is convex if for each x, yin S, the line \(\overline {xy} \) is contained in S.

So, the given statement is True.

02

Check for statement (b)

From theorem 8, if S and Trepresent a convex set, their intersection is also a convex set.

So, the given statement is True.

03

Check for statement (c)

According to theorem 10, every point in the set in \({\mathbb{R}^n}\), then every point in conv S can be represented as a convex combination. So, y can be expressed as,

\(y = {c_1}{{\bf{v}}_1} + {c_2}{{\bf{v}}_2} + ..... + {c_6}{{\bf{v}}_6}\)y=

It is a convex combination of \({{\bf{v}}_1}\), \({{\bf{v}}_2}\),….,\({{\bf{v}}_6}\).

So, the statement is True.

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Most popular questions from this chapter

Question: In Exercises \({\bf{5}}\) and \({\bf{6}}\), the matrix \(A\) is factored in the form \(PD{P^{ - {\bf{1}}}}\). Use the Diagonalization Theorem to find the eigenvalues of \(A\) and a basis for each eigenspace.

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

Question: Is \(\left( {\begin{array}{*{20}{c}}{ - 1 + \sqrt 2 }\\1\end{array}} \right)\) an eigenvalue of \(\left( {\begin{array}{*{20}{c}}2&1\\1&4\end{array}} \right)\)? If so, find the eigenvalue.

Suppose \({\bf{x}}\) is an eigenvector of \(A\) corresponding to an eigenvalue \(\lambda \).

a. Show that \(x\) is an eigenvector of \(5I - A\). What is the corresponding eigenvalue?

b. Show that \(x\) is an eigenvector of \(5I - 3A + {A^2}\). What is the corresponding eigenvalue?

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.\[A{\bf{=}}\left[{\begin{array}{*{20}{c}}{{\bf{10}}}&{\bf{7}}&{\bf{8}}&{\bf{7}}\\{\bf{7}}&{\bf{5}}&{\bf{6}}&{\bf{5}}\\{\bf{8}}&{\bf{6}}&{{\bf{10}}}&{\bf{9}}\\{\bf{7}}&{\bf{5}}&{\bf{9}}&{{\bf{10}}}\end{array}} \right]\]

(M)Use a matrix program to diagonalize

\(A = \left( {\begin{aligned}{*{20}{c}}{ - 3}&{ - 2}&0\\{14}&7&{ - 1}\\{ - 6}&{ - 3}&1\end{aligned}} \right)\)

If possible. Use the eigenvalue command to create the diagonal matrix \(D\). If the program has a command that produces eigenvectors, use it to create an invertible matrix \(P\). Then compute \(AP - PD\) and \(PD{P^{{\bf{ - 1}}}}\). Discuss your results.

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