Construct its corresponding Laplacian matrix
Given is the following graph
(1) Construct its corresponding Laplacian matrix.
(2) From the previous exercise sheet we know that {1, 2, 3}, {4, 5, 6} is (one of) the
best partition(s) into two classes. Construct the corresponding vector f.
Verify the equation
f>Lf = |V|.RatioCut(A, A hat)
for this particular choice of f.
Show that f is orthogonal to the all-one-vector and that ||f||^2 = n holds.
Homework Answers
Help with number 1 please! Programming for Math and Science Homework 4 Due by 11:59 p.m. Thursday, May 2, 2019 1. Find the eigenvalues and corresponding eigenvectors for the following matrices sin θ...
Help with number 1 please!
Programming for Math and Science Homework 4 Due by 11:59 p.m. Thursday, May 2, 2019 1. Find the eigenvalues and corresponding eigenvectors for the following matrices sin θ cos θ 0 0 4 Verify each calculation by hand and with Numpy. (For the second matrix, pick a value for 0 when using Numpy.) 2. Construct a 3 by 3 orthogonal matrix1. Determine its eigenvalues and find the eigenvector corresponding to the eigenvalue λ-1 3, Construct...
(0) is a lower- Consider the matrix equation Lx u, where L triangular square matrix and x = (p" a...
(0) is a lower- Consider the matrix equation Lx u, where L triangular square matrix and x = (p" and u = (u)' are column vectors. In view of Example 97: Solve the n equations for the n variables x1,x2, . . . , rn respectively. 1-12, . Example 97 We can find general formulas that characterize the procedure used in the previous example. Suppose we want to solve the equation Ux = v, where x = (x)' and v-(v)'...
Problem 2.2 n and let X ε Rnxp be a full-rank matrix, and Assume p Note that H is a square n × n ...
Please show all work in READ-ABLE way. Thank you so much in
advance.
Problem 2.2 n and let X ε Rnxp be a full-rank matrix, and Assume p Note that H is a square n × n matrix. This problem is devoted to understanding the properties H Any matrix that satisfies conditions in (a) is an orthogonal projection matriz. In this problem, we will verify this directly for the H given in (1). Let V - Im(X). (b) Show that...
0.5 0 0 5. Let P 0.5 0.6 0.3represent the probability transition matrix of a Markov...
0.5 0 0 5. Let P 0.5 0.6 0.3represent the probability transition matrix of a Markov chain with three 0 0.4 0.7 states (a) Show that the characteristic polynomial of P is given by P-ÀI -X-1.8λ2 +0.95λ-0.15) (b) Verify that λι 1, λ2 = 0.5 and λ3 = 0.3 satisfy the characteristic equation P-λ1-0 (and hence they are the eigenvalues of P) c) Show thatu3u2and u3are three eigenvectors corresponding to the eigenvalues λι, λ2 and λ3, respectively 1/3 (d) Let...
In this exercise, you will work with a QR factorization of an mxn matrix. We will proceed in the ...
In this exercise, you will work with a QR factorization of an mxn matrix. We will proceed in the way that is chosen by MATLAB, which is different from the textbook presentation. An mxn matrix A can be presented as a product of a unitary (or orthogonal) mxm matrix Q and an upper-triangular m × n matrix R, that is, A = Q * R . Theory: a square mxm matrix Q is called unitary (or orthogona) if -,or equivalently,...
Consider the following T is the reflection in the y-axis in R2: T(x, y) (-x, y),...
Consider the following T is the reflection in the y-axis in R2: T(x, y) (-x, y), v (2, -5) (a) Find the standard matrix A for the linear transformation T (b) Use A to find the image of the vector v (e) Sketch the graph of v and its image T (v) 5-4-3-21 T (v) T(v) 6 -5-4-3-2 6-5-4-3-2-1 239-lab 3 (2)pages F1 Assignment Submission For this assignment, you submit answers by question parts. The number of submissions remaining for...
1. For each of the following regression models, write down the X matrix and 3 vector....
1. For each of the following regression models, write down the X matrix and 3 vector. Assume in both cases that there are four observations (a) Y BoB1X1 + B2X1X2 (b) log Y Bo B1XiB2X2+ 2. For each of the following regression models, write down the X matrix and vector. Assume in both cases that there are five observations. (a) YB1XB2X2+BXE (b) VYBoB, X,a +2 log10 X2+E regression model never reduces R2, why 3. If adding predictor variables to a...
In this exercise you will work with LU factorization of an matrix A. Theory: Any matrix A can be ...
In this exercise you will work with LU factorization of an matrix A. Theory: Any matrix A can be reduced to an echelon form by using only row replacement and row interchanging operations. Row interchanging is almost always necessary for a computer realization because it reduces the round off errors in calculations - this strategy in computer calculation is called partial pivoting, which refers to selecting for a pivot the largest by absolute value entry in a column. The MATLAB...
Math 32-_ Multivariable Calculus HW 3 (1) Consider the two straight lines L1 : (2-t, 3...
Math 32-_ Multivariable Calculus HW 3 (1) Consider the two straight lines L1 : (2-t, 3 + 2t,-t) and L2 : <t,-2 + t, 7-20 a) Verify that L1 and L2 intersect, and find their point of intersection. (b) Find the equation of the plane containing L1 and L2 (2) Consider the set of all points (a, y, z) satisfying the equation 2-y2+220. Find their intersection 0 and 2-0. Use that information to sketch a with the planes y =-3,-2,-1,0,...
MATLAB EXERCISE 5 This exercise focuses on the Jacobian matrix and determinant, simulated resolved-rate control, and...
MATLAB EXERCISE 5 This exercise focuses on the Jacobian matrix and determinant, simulated resolved-rate control, and inverse statics for the planar 3-DOF, 3R robot. (See Figures 3.6 and 3.7; the DH parameters are given in Figure 3.8.) The resolved-rate control method [9] is based on the manipulator velocity equation x = kve, where ky is the Jacobian matrix, is the vector of relative joint rates, X is the vector of commanded Cartesian velocities (both translational and rotational), and k is...
Help with number 1 please!
Programming for Math and Science Homework 4 Due by 11:59 p.m. Thursday, May 2, 2019 1. Find the eigenvalues and corresponding eigenvectors for the following matrices sin θ cos θ 0 0 4 Verify each calculation by hand and with Numpy. (For the second matrix, pick a value for 0 when using Numpy.) 2. Construct a 3 by 3 orthogonal matrix1. Determine its eigenvalues and find the eigenvector corresponding to the eigenvalue λ-1 3, Construct...
(0) is a lower- Consider the matrix equation Lx u, where L triangular square matrix and x = (p" and u = (u)' are column vectors. In view of Example 97: Solve the n equations for the n variables x1,x2, . . . , rn respectively. 1-12, . Example 97 We can find general formulas that characterize the procedure used in the previous example. Suppose we want to solve the equation Ux = v, where x = (x)' and v-(v)'...
Please show all work in READ-ABLE way. Thank you so much in
advance.
Problem 2.2 n and let X ε Rnxp be a full-rank matrix, and Assume p Note that H is a square n × n matrix. This problem is devoted to understanding the properties H Any matrix that satisfies conditions in (a) is an orthogonal projection matriz. In this problem, we will verify this directly for the H given in (1). Let V - Im(X). (b) Show that...
0.5 0 0 5. Let P 0.5 0.6 0.3represent the probability transition matrix of a Markov chain with three 0 0.4 0.7 states (a) Show that the characteristic polynomial of P is given by P-ÀI -X-1.8λ2 +0.95λ-0.15) (b) Verify that λι 1, λ2 = 0.5 and λ3 = 0.3 satisfy the characteristic equation P-λ1-0 (and hence they are the eigenvalues of P) c) Show thatu3u2and u3are three eigenvectors corresponding to the eigenvalues λι, λ2 and λ3, respectively 1/3 (d) Let...
In this exercise, you will work with a QR factorization of an mxn matrix. We will proceed in the way that is chosen by MATLAB, which is different from the textbook presentation. An mxn matrix A can be presented as a product of a unitary (or orthogonal) mxm matrix Q and an upper-triangular m × n matrix R, that is, A = Q * R . Theory: a square mxm matrix Q is called unitary (or orthogona) if -,or equivalently,...
Consider the following T is the reflection in the y-axis in R2: T(x, y) (-x, y), v (2, -5) (a) Find the standard matrix A for the linear transformation T (b) Use A to find the image of the vector v (e) Sketch the graph of v and its image T (v) 5-4-3-21 T (v) T(v) 6 -5-4-3-2 6-5-4-3-2-1 239-lab 3 (2)pages F1 Assignment Submission For this assignment, you submit answers by question parts. The number of submissions remaining for...
1. For each of the following regression models, write down the X matrix and 3 vector. Assume in both cases that there are four observations (a) Y BoB1X1 + B2X1X2 (b) log Y Bo B1XiB2X2+ 2. For each of the following regression models, write down the X matrix and vector. Assume in both cases that there are five observations. (a) YB1XB2X2+BXE (b) VYBoB, X,a +2 log10 X2+E regression model never reduces R2, why 3. If adding predictor variables to a...
Math 32-_ Multivariable Calculus HW 3 (1) Consider the two straight lines L1 : (2-t, 3 + 2t,-t) and L2 : <t,-2 + t, 7-20 a) Verify that L1 and L2 intersect, and find their point of intersection. (b) Find the equation of the plane containing L1 and L2 (2) Consider the set of all points (a, y, z) satisfying the equation 2-y2+220. Find their intersection 0 and 2-0. Use that information to sketch a with the planes y =-3,-2,-1,0,...
MATLAB EXERCISE 5 This exercise focuses on the Jacobian matrix and determinant, simulated resolved-rate control, and inverse statics for the planar 3-DOF, 3R robot. (See Figures 3.6 and 3.7; the DH parameters are given in Figure 3.8.) The resolved-rate control method [9] is based on the manipulator velocity equation x = kve, where ky is the Jacobian matrix, is the vector of relative joint rates, X is the vector of commanded Cartesian velocities (both translational and rotational), and k is...
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