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Construction of minimum norm solution matrix

  1. Oct 8, 2009 #1
    1. The problem statement, all variables and given/known data
    Consider the linear system of equations Ax = b b is in the range of A
    Given the SVD of a random matrix A; construct a full rank matrix B for which the solution:
    x = B^-1*b
    is the minimum norm solution.

    Also A is rank deficient by a known value and diagonalizable

    2. Relevant equations



    3. The attempt at a solution
    I am completely clueless here. I know that due to rank deficiency some eigenvalues of A are zero and this has something to do with the corresponding left and righ singular vectors but I am clueless as to what. I have read through all our notes and can find nothing relating to this problem. Any hint to get me started would be appreciated.
     
  2. jcsd
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