Introduction to Algorithms
3rd Edition
ISBN: 9780262033848
Author: Thomas H. Cormen, Ronald L. Rivest, Charles E. Leiserson, Clifford Stein
Publisher: MIT Press
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Chapter D.2, Problem 2E
Program Plan Intro
To prove that the determinant of a lower and upper triangular matrix is equal to the product of its diagonal.
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Find the product of the product of the elements of a matrix and the other elements of a matrix with random integer elements of 4 x 2 each
. 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.
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
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- Given a square matrix A that is diagonalizable. Determine whether the matrix is diagonalizable. (It isn't allowed to use any direct command of Matlab or Python to find the eigenvalues and eigenvector of A). Give example for each case.arrow_forwardLet A be an m × n matrix with m > n. (a) What is the maximum number of nonzero singular values that A can have? (b) If rank(A) = k, how many nonzero singular values does A have?arrow_forwardOrthogonal linear operator : has the standard basis matrix: Find an orthonormal basis in which the operator matrix has a canonical form and write out this matrix. Specify the axis and angle of rotation defined by the operatorarrow_forward
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