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13-May-2025 18:35:01

svd_truncated_test():
  MATLAB/Octave version 9.11.0.2358333 (R2021b) Update 7
  Demonstrate the use of the truncated
  Singular Value Decomposition (SVD) for cases where
  the sizes of M and N are very different.

svd_truncated_u_test():
  M = 4
  N = 3

  Original matrix A:
    0.8147    0.6324    0.9575
    0.9058    0.0975    0.9649
    0.1270    0.2785    0.1576
    0.9134    0.5469    0.9706


  Maximum error |A - U*S*V'| = 6.66134e-16

  Recomputed A = U * S * V':
    0.8147    0.6324    0.9575
    0.9058    0.0975    0.9649
    0.1270    0.2785    0.1576
    0.9134    0.5469    0.9706


svd_truncated_v_test():
  M = 3
  N = 4

  Original matrix A:
    0.9572    0.1419    0.7922    0.0357
    0.4854    0.4218    0.9595    0.8491
    0.8003    0.9157    0.6557    0.9340


  Maximum error |A - U*S*V'| = 6.66134e-16

  Recomputed A = U * S * V':
    0.9572    0.1419    0.7922    0.0357
    0.4854    0.4218    0.9595    0.8491
    0.8003    0.9157    0.6557    0.9340


svd_truncated_test():
  Normal end of execution.

13-May-2025 18:35:01