since
by the definition of convexivity we have to show that
where
Now, { because, det (A+B) Det(A) +Det (B) }
{USING , log mp = log m +log p}
WHERE n is the order of the matrix
{because }
therefore
i.e .
hence f is convex
Let f(X) = −log|X| with the domain of f is the set of positive-definite matrices, denoted...
linear optimization Assume that f : D → R is twice continuously differentiable for all x D, where the domain D off is an open, convex subset of Rn. Sh ▽2f(x), is symmetric positive-semi-definite for all x E D if and only if f is a convex function on D Moreover, if its Hessian matrix. ▽2 (x), is symmetric positive-definite for all x E D, then f is a strictly convex function on D Show that the converse of this...
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)...
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)...
Let be a set. Show that the convex hull of , denoted by , is equal to the set We were unable to transcribe this imageWe were unable to transcribe this imagecvx(S) We were unable to transcribe this image cvx(S)
(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...
A function f : Rn λε [0,1] R is strictly convex if for all x, y є Rn and all fax + (1-λ)y) < λ/(x) + (1-1)f(y) A symmetric matrix P-AT +A is called positive-definite if all its eigenvalues are positive. Show that a quadratic function f(x) -xPx is a convex function if and only P is positive-definite. A function f : Rn λε [0,1] R is strictly convex if for all x, y є Rn and all fax +...
linear algebra Find all n x n orthogonal, symmetric, and positive definite real matrix (matrices). Explain answer
(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"...
Let A and B be square matrices and P be an invertible matrix. If A- PBP-,show that A and B have the same determinant. Let A and B be square matrices and P be an invertible matrix. If A- PBP-,show that A and B have the same determinant.
Exercise 1.4.61 This Exercise generalizes Propositions 1.4.51 and 1.4.53. Let A be an nxn positive definite matrix, let ji, j2, ..., jk be integers such that 1 < <j2 <... ik <n, and let X be the k x k matrix obtained by intersecting rows j1, ...,jk with columns 11,...,jk. Prove that A is positive definite.