Differential Equations: Computing and Modeling (5th Edition), Edwards, Penney & Calvis
5th Edition
ISBN: 9780321816252
Author: C. Henry Edwards, David E. Penney, David Calvis
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Question
Chapter 5.1, Problem 4P
Program Plan Intro
Program Description: Purpose ofproblem is to find the values of Ay and Bx and also check whether the products Ax and By is defined or not.
Summary introduction: Problem will use matrix multiplication in the matrices
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
3
: Prove that the sum of the three variables of the sum exponent f(x) = Σe is strictly convex. For this
i=1
purpose, compute the Hessian matrix of the function f(x).
Asap
(Cayley-IHamilton Theorem) The Cayley-Ilamilton theorem is a powerful theorem in
Linear algebra that states: every square matrix of real numbers satisfies its own char-
acteristic equation. For 2 x 2 matrices this can be seen in the following way. First, we
introduce the trace of the matrix
tr A
41,1 +22
and the determinant
det A = a11a22 - 41,22,1-
Then, the chacteristic polynomial is the quadratic given by
p(A) = x – (tr A)A + (det. A).
Then, for any 2 x 2 matrix, if you plug it into this polynomial, you should always get
a zero matrix.
c_h_test Function:
Input parameters:
• a single 2 x2 matrix for which you would like to test the Cayley Ilamilton
Theorem
Local Variables:
• two scalars to represent the trace and determinant
Output parameters:
a single 2 x2 which is the result of evaluating the charcteristic polynomial
at A (note: think carefully about the constant term)
A possible sample case is:
> mat_B = c_h_test([3, 2 ; 2, 0])
mat B =
0 0
Chapter 5 Solutions
Differential Equations: Computing and Modeling (5th Edition), Edwards, Penney & Calvis
Ch. 5.1 - Let A=[2347] and B=[3451]. Find (a) 2A+3B; (b)...Ch. 5.1 - Prob. 2PCh. 5.1 - Find AB and BA given A=[203415] and B=[137032].Ch. 5.1 - Prob. 4PCh. 5.1 - Prob. 5PCh. 5.1 - Prob. 6PCh. 5.1 - Prob. 7PCh. 5.1 - Prob. 8PCh. 5.1 - Prob. 9PCh. 5.1 - Prob. 10P
Ch. 5.1 - Prob. 11PCh. 5.1 - Prob. 12PCh. 5.1 - Prob. 13PCh. 5.1 - Prob. 14PCh. 5.1 - Prob. 15PCh. 5.1 - Prob. 16PCh. 5.1 - Prob. 17PCh. 5.1 - Prob. 18PCh. 5.1 - Prob. 19PCh. 5.1 - Prob. 20PCh. 5.1 - Prob. 21PCh. 5.1 - Prob. 22PCh. 5.1 - Prob. 23PCh. 5.1 - Prob. 24PCh. 5.1 - Prob. 25PCh. 5.1 - Prob. 26PCh. 5.1 - Prob. 27PCh. 5.1 - Prob. 28PCh. 5.1 - Prob. 29PCh. 5.1 - Prob. 30PCh. 5.1 - Prob. 31PCh. 5.1 - Prob. 32PCh. 5.1 - Prob. 33PCh. 5.1 - Prob. 34PCh. 5.1 - Prob. 35PCh. 5.1 - Prob. 36PCh. 5.1 - Prob. 37PCh. 5.1 - Prob. 38PCh. 5.1 - Prob. 39PCh. 5.1 - Prob. 40PCh. 5.1 - Prob. 41PCh. 5.1 - Prob. 42PCh. 5.1 - Prob. 43PCh. 5.1 - Prob. 44PCh. 5.1 - Prob. 45PCh. 5.2 - Prob. 1PCh. 5.2 - Prob. 2PCh. 5.2 - Prob. 3PCh. 5.2 - Prob. 4PCh. 5.2 - Prob. 5PCh. 5.2 - Prob. 6PCh. 5.2 - Prob. 7PCh. 5.2 - Prob. 8PCh. 5.2 - Prob. 9PCh. 5.2 - Prob. 10PCh. 5.2 - Prob. 11PCh. 5.2 - Prob. 12PCh. 5.2 - Prob. 13PCh. 5.2 - Prob. 14PCh. 5.2 - Prob. 15PCh. 5.2 - Prob. 16PCh. 5.2 - Prob. 17PCh. 5.2 - Prob. 18PCh. 5.2 - Prob. 19PCh. 5.2 - Prob. 20PCh. 5.2 - Prob. 21PCh. 5.2 - Prob. 22PCh. 5.2 - Prob. 23PCh. 5.2 - Prob. 24PCh. 5.2 - Prob. 25PCh. 5.2 - Prob. 26PCh. 5.2 - Prob. 27PCh. 5.2 - Prob. 28PCh. 5.2 - Prob. 29PCh. 5.2 - Prob. 30PCh. 5.2 - Prob. 31PCh. 5.2 - Prob. 32PCh. 5.2 - Prob. 33PCh. 5.2 - Prob. 34PCh. 5.2 - Prob. 35PCh. 5.2 - Prob. 36PCh. 5.2 - Prob. 37PCh. 5.2 - Prob. 38PCh. 5.2 - Prob. 39PCh. 5.2 - Prob. 40PCh. 5.2 - Prob. 41PCh. 5.2 - Prob. 42PCh. 5.2 - Prob. 43PCh. 5.2 - Prob. 44PCh. 5.2 - Prob. 45PCh. 5.2 - Prob. 46PCh. 5.2 - Prob. 47PCh. 5.2 - Prob. 48PCh. 5.2 - Prob. 49PCh. 5.2 - Prob. 50PCh. 5.3 - Prob. 1PCh. 5.3 - Prob. 2PCh. 5.3 - Prob. 3PCh. 5.3 - Prob. 4PCh. 5.3 - Prob. 5PCh. 5.3 - Prob. 6PCh. 5.3 - Prob. 7PCh. 5.3 - Prob. 8PCh. 5.3 - Prob. 9PCh. 5.3 - Prob. 10PCh. 5.3 - Prob. 11PCh. 5.3 - Prob. 12PCh. 5.3 - Prob. 13PCh. 5.3 - Prob. 14PCh. 5.3 - Prob. 15PCh. 5.3 - Prob. 16PCh. 5.3 - Prob. 17PCh. 5.3 - Prob. 18PCh. 5.3 - Prob. 19PCh. 5.3 - Prob. 20PCh. 5.3 - Prob. 21PCh. 5.3 - Prob. 22PCh. 5.3 - Prob. 23PCh. 5.3 - Prob. 24PCh. 5.3 - Prob. 25PCh. 5.3 - Prob. 26PCh. 5.3 - Prob. 27PCh. 5.3 - Prob. 28PCh. 5.3 - Prob. 29PCh. 5.3 - Prob. 30PCh. 5.3 - Prob. 31PCh. 5.3 - Prob. 32PCh. 5.3 - Prob. 33PCh. 5.3 - Verify Eq. (53) by substituting the expressions...Ch. 5.3 - Prob. 35PCh. 5.3 - Prob. 36PCh. 5.3 - Prob. 37PCh. 5.3 - Prob. 38PCh. 5.3 - Prob. 39PCh. 5.3 - Prob. 40PCh. 5.4 - Prob. 1PCh. 5.4 - Prob. 2PCh. 5.4 - Prob. 3PCh. 5.4 - Prob. 4PCh. 5.4 - Prob. 5PCh. 5.4 - Prob. 6PCh. 5.4 - Prob. 7PCh. 5.4 - Prob. 8PCh. 5.4 - Prob. 9PCh. 5.4 - Prob. 10PCh. 5.4 - Prob. 11PCh. 5.4 - Prob. 12PCh. 5.4 - Prob. 13PCh. 5.4 - Prob. 14PCh. 5.4 - Prob. 15PCh. 5.4 - Prob. 16PCh. 5.4 - Prob. 17PCh. 5.4 - Prob. 18PCh. 5.4 - Prob. 19PCh. 5.4 - Prob. 20PCh. 5.4 - Prob. 21PCh. 5.4 - Prob. 22PCh. 5.4 - Prob. 23PCh. 5.4 - Prob. 24PCh. 5.4 - Prob. 25PCh. 5.4 - Prob. 26PCh. 5.4 - Prob. 27PCh. 5.4 - Prob. 28PCh. 5.4 - Prob. 29PCh. 5.5 - Prob. 1PCh. 5.5 - Prob. 2PCh. 5.5 - Prob. 3PCh. 5.5 - Prob. 4PCh. 5.5 - Prob. 5PCh. 5.5 - Prob. 6PCh. 5.5 - Prob. 7PCh. 5.5 - Prob. 8PCh. 5.5 - Prob. 9PCh. 5.5 - Prob. 10PCh. 5.5 - Prob. 11PCh. 5.5 - Prob. 12PCh. 5.5 - Prob. 13PCh. 5.5 - Prob. 14PCh. 5.5 - Prob. 15PCh. 5.5 - Prob. 16PCh. 5.5 - Prob. 17PCh. 5.5 - Prob. 18PCh. 5.5 - Prob. 19PCh. 5.5 - Prob. 20PCh. 5.5 - Prob. 21PCh. 5.5 - Prob. 22PCh. 5.5 - Prob. 23PCh. 5.5 - Prob. 24PCh. 5.5 - Prob. 25PCh. 5.5 - Prob. 26PCh. 5.5 - Prob. 27PCh. 5.5 - Prob. 28PCh. 5.5 - Prob. 29PCh. 5.5 - Prob. 30PCh. 5.5 - Prob. 31PCh. 5.5 - Prob. 32PCh. 5.5 - Prob. 33PCh. 5.5 - Prob. 34PCh. 5.5 - Prob. 35PCh. 5.5 - Prob. 36PCh. 5.6 - Prob. 1PCh. 5.6 - Prob. 2PCh. 5.6 - Prob. 3PCh. 5.6 - Prob. 4PCh. 5.6 - Prob. 5PCh. 5.6 - Prob. 6PCh. 5.6 - Prob. 7PCh. 5.6 - Prob. 8PCh. 5.6 - Prob. 9PCh. 5.6 - Prob. 10PCh. 5.6 - Prob. 11PCh. 5.6 - Prob. 12PCh. 5.6 - Prob. 13PCh. 5.6 - Prob. 14PCh. 5.6 - Prob. 15PCh. 5.6 - Prob. 16PCh. 5.6 - Prob. 17PCh. 5.6 - Prob. 18PCh. 5.6 - Prob. 19PCh. 5.6 - Prob. 20PCh. 5.6 - Prob. 21PCh. 5.6 - Prob. 22PCh. 5.6 - Prob. 23PCh. 5.6 - Prob. 24PCh. 5.6 - Prob. 25PCh. 5.6 - Prob. 26PCh. 5.6 - Prob. 27PCh. 5.6 - Prob. 28PCh. 5.6 - Prob. 29PCh. 5.6 - Prob. 30PCh. 5.6 - Prob. 31PCh. 5.6 - Prob. 32PCh. 5.6 - Prob. 33PCh. 5.6 - Prob. 34PCh. 5.6 - Prob. 35PCh. 5.6 - Prob. 36PCh. 5.6 - Prob. 37PCh. 5.6 - Prob. 38PCh. 5.6 - Prob. 39PCh. 5.6 - Prob. 40PCh. 5.7 - Prob. 1PCh. 5.7 - Prob. 2PCh. 5.7 - Prob. 3PCh. 5.7 - Prob. 4PCh. 5.7 - Prob. 5PCh. 5.7 - Prob. 6PCh. 5.7 - Prob. 7PCh. 5.7 - Prob. 8PCh. 5.7 - Prob. 9PCh. 5.7 - Prob. 10PCh. 5.7 - Prob. 11PCh. 5.7 - Prob. 12PCh. 5.7 - Prob. 13PCh. 5.7 - Prob. 14PCh. 5.7 - Prob. 15PCh. 5.7 - Prob. 16PCh. 5.7 - Prob. 17PCh. 5.7 - Prob. 18PCh. 5.7 - Prob. 19PCh. 5.7 - Prob. 20PCh. 5.7 - Prob. 21PCh. 5.7 - Prob. 22PCh. 5.7 - Prob. 23PCh. 5.7 - Prob. 24PCh. 5.7 - Prob. 25PCh. 5.7 - Prob. 26PCh. 5.7 - Prob. 27PCh. 5.7 - Prob. 28PCh. 5.7 - Prob. 29PCh. 5.7 - Prob. 30PCh. 5.7 - Prob. 31PCh. 5.7 - Prob. 32PCh. 5.7 - Prob. 33PCh. 5.7 - Prob. 34P
Knowledge Booster
Similar questions
- Consider the following. -4 2 0 1 -3 A = 0 4 2 2 1 2 2 (a) Verify that A is diagonalizable by computing P AP. P-lAP = E (b) Use the result of part (a) and the theorem below to find the eigenvalues of A. Similar Matrices Have the Same Eigenvalues If A and B are similar n xn matrices, then they have the same eigenvalues. VAarrow_forwardThe meet of two zero-one matrices A and B is described as AAB = [ajj A bj] AvB = [aj A bijl] A v B = [aj v bijl A AB = [aj v bijl]arrow_forwardQ4: Write the parametric equation of revolution surface in matrix form only which generated by rotate a Bezier curve defined by the coefficient parameter in one plane only, for the x-axis [0,5, 10,4], y-axis [1,4,2,2] respectively, for u-0.5 and 0 = 45° Note: [the rotation about y-axis].arrow_forward
- Use MATLAB to create a program for Gaussian Elimination.Important inclusions of the program:a. c0efficient and c0nstant matrices are separated.b. it can work on any size of matrixc. outputs the augmented matrix of the c0efficient and c0nstant matrices.d. outputs the R0w echel0n forme. outputs the soluti0n of systems of linear equati0ns using back substituti0nf. outputs the Reduced R0w echel0n form to verify answer in letter e.arrow_forward. The determinant of an n X n matrix can be used in solving systems of linear equations, as well as for other purposes. The determinant of A can be defined in terms of minors and cofactors. The minor of element aj is the determinant of the (n – 1) X (n – 1) matrix obtained from A by crossing out the elements in row i and column j; denote this minor by Mj. The cofactor of element aj, denoted by Cj. is defined by Cy = (-1y**Mg The determinant of A is computed by multiplying all the elements in some fixed row of A by their respective cofactors and summing the results. For example, if the first row is used, then the determi- nant of A is given by Σ (α(CI) k=1 Write a program that, when given n and the entries in an n Xn array A as input, computes the deter- minant of A. Use a recursive algorithm.arrow_forward#1 In this sequence of problems, we will generate random matrices (2d arrays), and calculate the product by using by both inner and outer product methods and then compare them with the product implemented in numpy. Verify that a matrix multiplied by a column vector is simply a linear combination of the columns of the matrix. Namely, if the columns of the matrix A are a_1, a_2, .. a_n and the vector x is (x_1,... x_n), then Ax = x_1 a_1 + ... + x_n a_n. Explain why this is simply the outer product way of multiplying A and x.arrow_forward
- Find the eigenvalues of the matrix and determine whether there is a sufficient number to guarantee that the matrix is diagonalizable. (Recall that the matrix may be diagonalizable even though it is not guaranteed to be diagonalizable by the theorem shown below.) Sufficient Condition for Diagonalization If an n xn matrix A has n distinct eigenvalues, then the corresponding eigenvectors are linearly independent and A is diagonalizable. Find the eigenvalues. (Enter your answers as a comma-separated list.) Is there a sufficient number to guarantee that the matrix is diagonalizable? O Yes O No Need Help? Read itarrow_forwardAnswer the question using Python programming language and Numpy:arrow_forwardGenerate H (Hilbert Matrix) for n = 15.Compute the right-hand size vector b = Hx so that the exact solution is xˆ = 1 (thevector of ones). Solve the linear system in MATLAB as a least squares problem usingSVD and report the relative error in the approximate solution in the Euclidean norm.Compare your result to the solution obtained by H\b.arrow_forward
- Find the characteristic equation and the eigenvalues (and a basis for each of the corresponding eigenspaces) of the matrix. 2 -2 3 -2 -1 (a) the characteristic equation (b) the eigenvalues (Enter your answers from smallest to largest.) (21, 22, 13) = a basis for each of the corresponding eigenspaces X1 = X2 = Need Help? Read It Watch Itarrow_forward(a) Suppose the matrix A is m × n and suppose that b is in the range of A. Give a formula for all solutions to the equation Ax = b in terms of the SVD of A, when m≥n and A has rank parrow_forwardsolve:arrow_forwardarrow_back_iosSEE MORE QUESTIONSarrow_forward_ios
Recommended textbooks for you
Operations Research : Applications and AlgorithmsComputer ScienceISBN:9780534380588Author:Wayne L. WinstonPublisher:Brooks Cole
Operations Research : Applications and Algorithms
Computer Science
ISBN:9780534380588
Author:Wayne L. Winston
Publisher:Brooks Cole