Problem 2. In this problem we consider the question of whether a small value of the residual kAz − bk means that z is a good approximation to the solution x of the linear system Ax = b. We showed in class that, kx − zk kxk ≤ kAkkA −1 k kAz − bk kbk . which implies that if the condition number kAkkA−1k of A is small, a small relative residual implies a small relative error in the solution. We now show computationally what can happen if the condition number is large. A standard example of a matrix that is ill-conditioned is the Hilbert matrix H, with entries (Hij ) = 1/(i+j−1). For n = 8, 12, 16 (where H is of dimension n×n), use Matlab to solve the linear system of equations Hx = b, where b is the vector Hy and y is the vector with yi = 1/ √ n, i = 1 . . . n. Clearly, the true solution is given by x = y, and we let z denote the approximation obtained by Matlab. Then calculate for each value of n the following quantities: (i) the relative error kx − zk/kxk, (ii) the relative residual kHz − bk2/kbk, (iii) the condition number kHkkH−1k, and (iv) the product of the quantities in (ii) and (iii). Arrange all these numbers in a table. The Matlab commands 1 norm and cond can be used to compute the norm and condition numbers, respectively. When vectors are input, Matlab writes them as row vectors. To convert y to a column vector, write it as y 0 . To solve the linear system Hz = b in Matlab, type z = H \ b. An example of a Matlab loop is given below; the semicolon keeps Matlab from writing unwanted output to the screen. To avoid potential problems, type clear before running a new value of n. Example of a Matlab Loop: for i=1:10 y(i) = 1/sqrt(10); end
Problem 2. In this problem we consider the question of whether a small value of the...
My question is from the first step from where did we get 2 ? EXAMPLE 2.21 FIRST-ORDER RECURSIVE SYSTEM (CONTINUED): COMPLETE SOLUTION Find the solution for the first-order recursive system described by the difference equation y[n] - Laxn – 1] = x[n] (2.46) if the input is x[n] = (1/2)*u[n] and the initial condition is y[ – 1] = 8. Solution: The form of the solution is obtained by summing the homogeneous solution determined in Example 2.18 with the particular...
If A is an m × n matrix, and x is an n × 1 vector, then the linear transformation y = Ar maps R" to R", so the linear transformation should have a condition number, condar (x). Assume that |I-ll is a subordinate norm. a. Show that we can define condar (x)-|All llrI/IAxll for every x 0. b. Find the condition number of the linear transformation at[ 2] using the oo-norm. c. Show that condAr(x) IIA for all x....
If A is an m × n matrix, and x is an n × 1 vector, then the linear transformation y = Ar maps R" to R", so the linear transformation should have a condition number, condar (x). Assume that |I-ll is a subordinate norm. a. Show that we can define condar (x)-|All llrI/IAxll for every x 0. b. Find the condition number of the linear transformation at[ 2] using the oo-norm. c. Show that condAr(x) IIA for all x....
Intro Step 11 We will be working with the following matrix [1 2 3 0 0 0 0 2 1 2 3 0 0 0 3 2 1 2 3 0 0 0 3 2 1 2 3 0 0 0 3 2 1 2 3 0 0 0 3 2 1 2 0 0 0 0 3 2 1 0 0 0 0 0 3 2 0] 0 0 0 0 3 2 1 Use MATLAB to find the...
2. Linear dependence of vectors: If we want to describe any vector in three dimensions, we need a basis of three vectors, and we usually choose i,j. k, the unit vectors in the r, y, z directions. We could equally well have chosen for example a = i+5, b = i-j and c = i+2] _ k. Then the vector v = 41+2] _ k would be expressed as v = 3a + )b-c a, b, c form a suitable...
4. We have n statistical units. For unit i, we have (x; yi), for i 1,2,...,n. We used the least squares line to obtain the estimated regression line bobi . (a) Show that the centroid (z, y) is a point on the least squares line, where x-(1/n) Σ-Χί and у-(1/ n) Σ|-1 yi. (Hint: Evaluate the line at x x.) (b) In the suggested exercises, we showed that e,-0 and where e is the ith residual, that is e -y...
Using hand work for the parts with a paper next to them, and MatLab for the parts with the MatLab logo next to them, complete the following: Consider the linear BVP 4y " + 3y , + y = 0, 0<x<1 y(0)1 You will define a set of linear equations for yi,0, (yi y(Xi), 1 = o,.. . ,n) and the set of nodes is with xi-ih, 1-0, . . . , n and h =-. n is a fixed...
(1 point) Solve the Bernoulli initial value problem - 2 'y', y(1)=2 For this example we haven We obtain the equation + given by Solving the resulting first order linear equation for u we obtain the general solution with arbitrary constant Then transforming back into the variables 2 and y and using the initial condition to find C Finally we obtain the explicit solution of the initial value problem as
In this exercise we consider finding the first five coefficients in the series solution of the first order linear initial value problem (+3)y' 2y 0 subject to the initial condition y(0) 1. Since the equation has an ordinary point at z 0 it has a power series solution in the form We learned how to easily solve problems like this separation of variables but here we want to consider the power series method (1) Insert the formal power series into...
In this exercise we consider the second order linear equation y" therefore has a power series solution in the form 4y = 0. This equation has an ordinary point at x = 0 and We learned how to easily solve problems like this in several different ways but here we want to consider the power series method (1) Insert the formal power series into the differential equation and derive the recurrence relation Cn-2 for n - 2, 3, NOTE co...