  We study the performance of gradient-descent optimization to estimate the
coefficients of the discrete-time first-order regular perturbation (FRP). With
respect to numerically computed coefficients, the optimized coefficients yield
a model that (i) extends the FRP range of validity, and (ii) reduces the
model's complexity.
