Linear Algebra help! 2. Find the QR-decomposition of the following matrix: A= 2 21 2 2...
1-1 1 (1 2) 1.4) Find the QR decomposition of the matrix A = | 1 1-1 1 (1 2) 1.4) Find the QR decomposition of the matrix A = | 1
linear algebra Thank you for the help. (3) Find the QR factorization of A. T 2 31 2 4 1,b= 1 1 1 [1] 2 1 Given: A =
1. (4) Find the QR decomposition of the matrix A = -1 0 2 1
Please Urgent help me!!!(QR decomposition queastion) You have not to solve all parts of question!!! The QR decomposition can be used to solve a linear system. Let A be an n x n matrix, with A system Axb can be written as QR. Then, the linear QRx = b The process goes as follows Solve Qy b for y Solve Rx-y for x a. It is very easy to solve for y without using Gaussian elimination. Why? b. The solution...
7. Consider the following matrix (a) Find the QR decomposition of A using the Gram Schmidt process. (b) Use the QR decomposition from (a) to find the least-squares solution to Ax = b where -3 7. Consider the following matrix (a) Find the QR decomposition of A using the Gram Schmidt process. (b) Use the QR decomposition from (a) to find the least-squares solution to Ax = b where -3
4. Find a QR-factorization of the matrix 5. Find an LU-decomposition of the matrix A =
Find the QR decomposition of the following matrix: [1,2,5;-1,1,4;-1,4,-3;1,-4,7;1,2,1]
(4.2) Let 4 7 A= 4 7 -2 1 (a) Find the QR decomposition of A. It has to be of the form A QR where Q is a 3 x 3 orthogonal matrix, and R is 3 x 2 upper-triangular. (b) Use part (a) to find the least squares solution to the -6 Ax -4 -2
linear algebra 2. (25 points) Find an orthogonal basis for the column space of the following matrix, [101] 1 0 1 1 1 1 1 0
linear algebra 3. Suppose that A is a 2 x 2 matrix: (a) Find Az if r = (13) is an eigenvector with eigenvalue 1 = 3. (b) Is it possible for A to have 3 eigenvalues? Why or why not? (C) True/False: If is an eigenvalue of A, there are infinitely many eigenvectors with eigenvalue .. (d) True/False: If I = 0) is an eigenvalue, then Eo = Nul (A).