Infinite-dimensional operator ridgelet transform

8. Numerical experiments🔗

Three experiments illustrate the sampling step of Theorem 6.8 and Theorem 6.6, and the explicit transforms in Example 7.2 and Example 7.6. The input spaces are \ell^2 and L^2(0,1), represented numerically by finitely many coordinates. Varying that resolution tests the sensitivity of the observed errors; these finite computations do not prove a uniform-in-dimension theorem.

Errors are supremum errors over finite test sets, averaged over independent trials. Appendix E records the seed, sampling laws, numerical integration and evaluation procedures.

  1. 8.1. Experiment 1: ReLU with Gaussian random directions
  2. 8.2. Experiment 2: synthesis of the weighted Gaussian target
  3. 8.3. Experiment 3: the Dirichlet operator layer
  4. 8.4. Approximation-error summary