02-Jun-2023 11:28:05

svd_truncated_test():
  MATLAB/Octave version 5.2.0
  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:
   0.215129   0.884469   0.386528
   0.074237   0.152296   0.016673
   0.282038   0.869561   0.271391
   0.141344   0.805023   0.852227

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

  Recomputed A = U * S * V':
   0.215129   0.884469   0.386528
   0.074237   0.152296   0.016673
   0.282038   0.869561   0.271391
   0.141344   0.805023   0.852227

svd_truncated_v_test():
  M = 3
  N = 4

  Original matrix A:
   0.557730   0.309081   0.081118   0.913477
   0.680330   0.538436   0.656826   0.923637
   0.309444   0.390714   0.138950   0.343789

  Maximum error |A - U*S*V'| = 5.55112e-16

  Recomputed A = U * S * V':
   0.557730   0.309081   0.081118   0.913477
   0.680330   0.538436   0.656826   0.923637
   0.309444   0.390714   0.138950   0.343789

svd_truncated_test():
  Normal end of execution.

02-Jun-2023 11:28:05