Let \(A=\left[\begin{array}{ccc}2 & 0 & -1 \\ 1 & -5 & 1 \\ 2 & -7 & 1\end{array}\right]\)
a) Compute \(A^{-1} .\)
b) Use \(A^{-1}\) to solve the following system of linear exuations:
$$ \begin{array}{r} 2 x_{1}+-x_{3}=3 \\ x_{1}-5 x_{2}+x_{3}=1 \\ 2 x_{1}-7 x_{2}+x_{3}=4 \end{array} $$
Problem on Linear programming and Simplex methodThe \(\ell_{1}\) norm of a vector \(v \in \mathbb{R}\) is defined by$$ \|v\|_{1}:=\sum_{i=1}^{n}\left|v_{i}\right| $$Problems of the form Minimize \(\|v\|_{1}\) subject to \(v \in \mathbb{R}^{n}\) and \(A v=b\) arise very frequently in applied math, particularly in the field of compressed sensing.Consider the special case of this problem whith \(n=3\),$$ A=\left(\begin{array}{lll} 1 & 1 & 0 \\ 3 & 0 & 1 \end{array}\right) \quad \text { and } \quad b=\left(\begin{array}{l} 3 \\ 8 \end{array}\right) $$(a) (3...
Problem settingConsider the linear transformation \(\phi(\cdot): \mathbb{R}^{2} \rightarrow \mathbb{R}^{2}\) on the standard vector space of dimension two over the field of real numbers defined as:$$ \phi\left(\left(\begin{array}{l} x_{0} \\ x_{1} \end{array}\right)\right)=\left(\begin{array}{r} 3 x_{0}-x_{1} \\ -7 x_{0}+2 x_{1} \end{array}\right) $$Problem taskFind \(\mathcal{R}_{G \rightarrow E}(\) id \()\) that is the change of basis matrix from basis \(G\) to the standard basis \(E\) where the standard basis vectors are:$$ \begin{array}{l} \vec{e}_{0}=\left(\begin{array}{l} 1 \\ 0 \end{array}\right) \\ \vec{e}_{1}=\left(\begin{array}{l} 0 \\ 1 \end{array}\right) \end{array} $$given that...
Let \(T: R^{3} \rightarrow R^{2}\) defined by \(T\left(\left[\begin{array}{l}x_{1} \\ x_{2} \\ x_{3}\end{array}\right]\right)=\left[\begin{array}{c}2 x_{1}+x_{3} \\ -x_{2}\end{array}\right]\).a. Find the matrix \(A\) such that \(T(x)=A x\)b. Demonstrate that \(T\) is a linear transformation.
Consider the following linear fractional program (LFP):$$ \begin{array}{ll} \max f\left(x_{1}, x_{2}\right)= & \frac{10 x_{1}+20 x_{2}+10}{3 x_{1}+4 x_{2}+20} \\ \text { s.t. } \quad & x_{1}+3 x_{2} \leq 50 \\ & 3 x_{1}+2 x_{2} \leq 80 \\ & x_{1}, x_{2} \geq 0 \end{array} $$(a) Transform this problem into an equivalent linear program.(b) Use Matlab (or other software) to solve the LP you created in part (a).(c) Use your answer from part (a) to find a solution to the original LFP.(d) Does...
Solve the system: \(x^{\prime}=3 x+5 y, y^{\prime}=-x-y\)Find the general solution to$$ \vec{x}^{\prime}=\left(\begin{array}{ll} 2 & 1 \\ 0 & 2 \end{array}\right) \vec{x} $$Find the general solution to$$ \vec{x}^{\prime}=\left(\begin{array}{ccc} 3 & 0 & -2 \\ 0 & 5 & 0 \\ 2 & 0 & 3 \end{array}\right) \vec{x} $$
Consider the linear system \(A x=b\) where \(A=\left[\begin{array}{rr}2 & -1 \\ -1 & 2\end{array}\right], b=\left[\begin{array}{l}1 \\ 1\end{array}\right], x=\left[\begin{array}{l}1 \\ 1\end{array}\right]\).We showed in class, using the eigenvlaues and eigenvectors of the iteration matrix \(M_{G S}\), that for \(x^{(0)}=\left[\begin{array}{ll}0 & 0\end{array}\right]^{T}\) the error at the \(k^{t h}\) step of the Gauss-Seidel iteration is given by$$ e^{(k)}=\left(\frac{1}{4}\right)^{k}\left[\begin{array}{l} 2 \\ 1 \end{array}\right] $$for \(k \geq 1\). Following the same procedure, derive an analogous expression for the error in Jacobi's method for the same system.
3. (3pts) Consider the \(3 \times 3\) matrices \(B=\left[\begin{array}{ccc}1 & 1 & 2 \\ -1 & 0 & 4 \\ 0 & 0 & 1\end{array}\right]\) and \(A=\left[\begin{array}{lll}\mathbf{a}_{1} & \mathbf{a}_{2} & \mathbf{a}_{3}\end{array}\right]\), where \(\mathbf{a}_{1}\), \(\mathbf{a}_{2}\), and \(\mathrm{a}_{9}\) are the columns of \(A\). Let \(A B=\left[\begin{array}{lll}v_{1} & v_{2} & v_{3}\end{array}\right]\), where \(v_{1}, v_{2}\), and \(v_{3}\) are the columns of the product. Express a as a linear combination of \(\mathbf{v}_{1}, \mathbf{v}_{2}\), and \(\mathbf{v}_{3}\).4. (3pts) Let \(T(x)=A x\) be the linear transformation given by$$...
(c) Let \(\mathbf{A}=\left[\begin{array}{ccc}1 & 1 & 1 \\ 2 & c & 0 \\ -2 & 1 & c\end{array}\right]\), where \(c\) is a real constant.(i) Use the adjoint method to find \(\mathbf{A}^{-1}\).(ii) \(\underline{\text { WITHOUT }}\) computing adj \(\left(\mathbf{A}^{\mathrm{T}}\right)\) or \((R+2) \operatorname{adj}\left(\mathbf{A}^{\mathrm{T}}\right)\), find \(\operatorname{det}\left((R+2) \operatorname{adj}\left(\mathbf{A}^{\mathrm{T}}\right)\right)\).(Note: The answers of (c)(i) and (ii) are in terms of \(c\).)
This problem uses least squares to find the curve \(y=a x+b x^{2}\) that best fits these 4 points in the plane:$$ \left(x_{1}, y_{1}\right)=(-2,2), \quad\left(x_{2}, y_{2}\right)=(-1,1), \quad\left(x_{1}, y_{3}\right)=(1,0), \quad\left(x_{4}, y_{4}\right)=(2,2) . $$a. Write down 4 equations \(a x_{i}+b x_{i}^{2}=y_{i}, i=1,2,3,4\), that would be true if the line actually went through a11 four points.b. Now write those four equations in the form \(\mathbf{A}\left[\begin{array}{l}a \\ b\end{array}\right]=\mathbf{y}\)c. Now find \(\left[\begin{array}{l}\hat{a} \\ \hat{b}\end{array}\right]\) that minimizes \(\left\|A\left[\begin{array}{l}a \\ b\end{array}\right]-\mathbf{y}\right\|^{2}\).
Problem A:A Markov chain \(X_{0}, X_{1}, X_{2}, \ldots\) with state space \{0,1,2\} has the following transition matrix$$ \boldsymbol{P}=\begin{array}{cccc} & 0 & 1 & 2 \\ 0 & 0.1 & 0.2 & a \\ 1 & 0.9 & 0.1 & 0 \\ 2 & 0.1 & 0.8 & b \end{array} $$and initial distribution \(\alpha_{0}=P\left(X_{0}=0\right)=0.3, \alpha_{1}=P\left(X_{0}=1\right)=0.4,\) and \(\alpha_{2}=P\left(X_{0}=2\right)=\)c. Find the following:a) values \(a, b\) and \(c\).b) \(P\left(X_{0}=0, X_{1}=1, X_{2}=2\right)\) and \(P\left(X_{0}=0, X_{1}=2, X_{2}=1\right)\).c) \(P\left(X_{1}=2\right)\)d) \(P\left(X_{2}=1, X_{3}=1 \mid X_{1}=2\right)\) and \(P\left(X_{1}=1, X_{2}=1 \mid...