a)Give that A is a positive definite matrix then A is diagonalizable. Then there exist orthogonal matrix Q (QT Q = I, identity matrix) and a diagonal matrix D such that D = QT D Q. Where the eigen values of A and D are same ( diagonal entries of D are eigen values of A and |A| = |D| ). Let B be non negative definite matrix. Consider A + B, we have
|QT (A+B) Q| = |QT |.|A+B|.|Q| = |A+B|, since |QT |.|Q| = |QT Q| = | I | = 1.
Therefore |A+B| = |QT (A+B) Q| = |QT A Q + QTB Q| = | D + QT B Q| ≥ |D|. Since B has non negative eigen values D + QT B Q has eigen values greater than D, thus the determinant is greater than D hence greater than A. Therefore |A+B| ≥ |A|. Equality occurs only when eigen values of B are all zero, since B is diagonalizable we must have B = (0).
b) In the above result replace A by B and B by A-B then we get
|B| ≤ |B + (A-B)| = |A| , i.e |A| ≥ |B| and equality occurs when A-B = (0), i.e A =B.
3.52 Let A be an mxm positive definite matrix and B be an mxm nonnegative definite matrix.
3.52 Let A be an mxm positive definite matrix and B be an mxm nonnegative definite matrix. 3.51 Show mal Il A IS à nonnegative definite matrix and a 0 for some z, then ai,-G3 = 0 for all j definite matrix. (a) Use the spectral decomposition of A to show that 3.52 Let A be an m x m positive definite matrix and B be an m × m nonnegative with equality if and only if B (0). (b)...
Question 2 Suppose A e Rxk is symmetric matrix. Let be the spectral decomposition. If λι,.. .λk are al nonzero, show that where At Question 2 Suppose A e Rxk is symmetric matrix. Let be the spectral decomposition. If λι,.. .λk are al nonzero, show that where At
A. (For Math 603 students only) Consider a symmetric and positive definite matrix A Rnxn and let λ'nin(A) and Xmax(A) be the minimal and maximal real eigenvalues of A respectively. Show that Suggested readings: Sections 7.2, 7.5, 7.6 A. (For Math 603 students only) Consider a symmetric and positive definite matrix A Rnxn and let λ'nin(A) and Xmax(A) be the minimal and maximal real eigenvalues of A respectively. Show that Suggested readings: Sections 7.2, 7.5, 7.6
(f) Let A be symmetric square matrix of order n. Show that there exists an orthogonal matrix P such that PT AP is a diagonal matrix Hint : UseLO and Problem EK〗 (g) Let A be a square matrix and Rn × Rn → Rn is defined by: UCTION E AND MES FOR THE la(x, y) = хтАУ (i) Show that I is symmetric, ie, 14(x,y) = 1a(y, x), if a d Only if. A is symmetric (ii) Show that...
A real symmetric matrix B e Rnxn (i.e. BT = B) is said to be positive definite if all of its eigenvalues 11, 12, ..., In are positive. (Recall that is an eigenvalue of B if and only if there exits a nonzero vector t such that Bt = it). Show that B-1 is also positive definite. That is, you need to show that all the eigenvalues of B-1 are also positive. (Hint: consider equation Bt; = liti for all...
3. Let V be a finite dimensional vector space with a positive definite scalar product. Let A: V-> V be a symmetric linear map. We say that A is positive definite if (Av, v) > 0 for all ve V and v 0. Prove: (a) if A is positive definite, then all eigenvalues are > 0. (b) If A is positive definite, then there exists a symmetric linear map B such that B2 = A and BA = AB. What...
(a) Let S be a symmetric positive definite matrix and define a function | on R" by 1/2 xx Sx . Prove that this function defines a vector norm. Hint: Use the Cholesky decomposition. (b) Find an example of square matrices A an This shows that ρ(A) is not a norm. Note: there are very simple examples. d B such that ρ(A+B)>ρ(A) + ρ(8) (a) Let S be a symmetric positive definite matrix and define a function | on R"...
3. Answer the following questions regarding positive definite matrix. A symmetric real matrix M is said to be positive definite if the scalar 27 Mz is positive for every non-zero column vector z (a) Consider the matrix [9 6] A = 6 a so that the matrix A is positive definite? What should a satisfy (b) Suppose we know matrix B is positive definite. Show that B1 is also positive definite. Hint use the definition and the fact that every...
(a) Let A be a Hermitian matrix. DEFINE: A is positive definite. (b) Let A be an n × n Hermitian matrix. PROVE: If A is positive definite the n every eigenvalue of A is positiv e. (c) Let Abe an n X n Hermitian matrix. PROVE: If every eigenvalue of A is positive. Then A is positive definite. (a) Let A be a Hermitian matrix. DEFINE: A is positive definite. (b) Let A be an n × n Hermitian...
Question 3 Set Let A-Σ 1 λ¡ViuT be the spectral decomposition with positive eigenvalues λ1,···Ae > 0. Ak Prove the following properties: 1. AT İs symmetric and AT PAP is its spectral decomposition: 3, Denote A-2-(A*) . Then A 2 E 1 where Question 3 Set Let A-Σ 1 λ¡ViuT be the spectral decomposition with positive eigenvalues λ1,···Ae > 0. Ak Prove the following properties: 1. AT İs symmetric and AT PAP is its spectral decomposition: 3, Denote A-2-(A*) ....