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Numerical Analysis - August 2022

Problem 1

(10 points) If A ∈ ℝ n × n is symmetric and positive definite, show that

| a i , j | ≤ 1 2 ( a i , i + a j , j )

holds for all 1 ≤ i , j ≤ n .

Problem 2

(10 points) Let A ∈ ℂ m × n with m ≥ n . Show that A * A is nonsingular if and only if A has full rank.

Problem 3

(10 points) Let A ∈ ℂ m × m , and let a j be its jth column. Prove the following inequality:

| det ( A ) | ≤ ∏ j = 1 m ∥ a j ∥ 2 .

Problem 4

Let

T = ( 4 1 0 1 2 − 1 0 − 1 3 ) .

  1. (5 points) Use Gerschgorin’s disk theorem to show that T is positive semidefinite.
  2. (5 points) Without computing the eigenvalues, explain why these eigenvalues are real.

Problem 5

Let

B = ( 3 − 6 41 / 5 0 1 1 4 − 8 63 / 5 ) .

  1. (10 points) Find the QR decomposition of B using the Gram-Schmidt orthogonalization process.
  2. (10 points) Write down the unitary Householder reflector matrix that you should multiply against B in order to zero out all but the first entry of its first column.

Problem 6

Consider the following linear system,

A x = F , ( 1 )

where

A = [ 2 − 1 0 ⋯ ⋯ 0 − 1 2 − 1 0 ⋯ 0 0 − 1 2 − 1 ⋱ ⋮ ⋮ ⋱ ⋱ ⋱ ⋱ ⋮ ⋮ ⋯ 0 − 1 2 − 1 ⋯ ⋯ ⋯ 0 − 1 2 ] .

  1. (10 points) Prove that the n × n tridiagonal matrix A is symmetric, positive definite (SPD).
  2. (10 points) Let B be a tridiagonal SPD matrix in the form of the matrix A. Prove that the Cholesky factor L of B has nonzero entries only along the main diagonal and the sub-diagonal lines, where B = L L t . Give the formula for L.
  3. (10 points) Design an O ( n ) algorithm to solve the linear system A x = F .

Problem 7

(10 points) Let x j ∈ ℝ m be the j-th column of X ∈ ℝ m × n be given. Let y ∈ ℝ m and λ > 0 also be given. Given a vector w ∈ ℝ n , define the following function

J ( w ) = ∥ X w − y ∥ 2 2 + λ ∥ w ∥ 1 ,

where ∥ ⋅ ∥ 2 and ∥ ⋅ ∥ 1 denote the 2- and 1-norm in ℝ n , respectively. Letting the i-th component w i of w vary and the other components of w be fixed, consider the following one-variable minimization problem reduced from J ( w ) :

min w i f ( w i ) ≡ min w i ∥ ∑ j = 1 n w j x j − y ∥ 2 2 + λ | w i | + λ ∑ j ≠ i | w j | = min w i ∥ w i x i + r ∥ 2 2 + λ | w i | + C = min w i ∑ j = 1 m ( w i x j i + r j ) 2 + λ | w i | + C , ( 2 )

where r ≡ ∑ j ≠ i w j x j − y is in ℝ m with r = ( r k ) m × 1 , and C = λ ∑ j ≠ i | w j | . Show that the optimal solution w i * for the minimization problem (2) is given by

w i * = { 0 if | a | ≤ λ , − λ + a b if − λ + a b > 0 , λ + a b if λ + a b < 0 ,

where a = − ∑ j = 1 m 2 x j i r j and b = ∑ j = 1 m 2 x j i 2 .