MATH661 Homework 4 - SVD applications

Posted: 09/15/21

Due: 09/22/21, 11:55PM

Building upon H03, this assigment focuses on operator approximations using the SVD.

1Track 1

  1. Transform the MATH661/images/Frida_Kahlo_96.png image, Fig. 1, into a matrix 𝑨 of gray scale values. Compute the SVD of 𝑨=𝑼𝚺𝑽T. Define

    𝑨p=i=1pσi𝒖i𝒗iT.

    Represent as images 𝑨p for p=10k,k=1,2,3,4. Comment on what you observe.

    Figure 1. Images to be represented as matrices

  2. Transform the MATH661/images/Georges_Seurat_3.png image, Fig. 1, into a matrix 𝑩 of gray scale values. Compute the SVD of 𝑩=𝑾𝚲𝑿T. Let r=rank(𝑩). Define

    𝑪p,q=i=1pσi𝒖i𝒗iT+i=r-q+1rλi𝒘i𝒙iT.

    Represent as images 𝑪p,q for p=10k,q=5k,k=1,2,3,4. Comment on what you observe.

  3. Revisit Problem 2 of H03. Instead of using the built-in least sqaures solver 𝒙=𝑨\𝒚, use the SVD of 𝑨 to solve the least squares problem as 𝒙=𝑨+𝒚.

2Track 2

  1. Matrices 𝑨,𝑩m×m are unitarily equivalent if 𝑸 unitary such that 𝑨=𝑸𝑩𝑸.

    1. Do unitarily equivalent 𝑨,𝑩 represent the same linear mapping?

    2. Prove: 𝑨,𝑩 unitarily equivalent implies they have the same singular values.

    3. Is the converse of (b) true?

  2. Use the SVD to prove that any 𝑨m×m is the limit of a sequence of matrices of full rank.

  3. Using the SVD 𝑨=𝑼𝚺𝑽, 𝑨m×n, define

    𝑨p=i=1pσi𝒖i𝒗i,p,prank(𝑨).

    Prove

    ||𝑨-𝑨p||2=inf𝑩m×n||𝑨-𝑩||.
  4. Solve Problem 1 & 2, Track 1.