Suppose I have the following function:

Here `x`

is the input, and `a_i`

and `omega`

are the parameters (so there are `n+2`

parameters in total).

Let’s say `n = 10`

. I want to find the best parameters that will fit the training dataset `(y_i, f(x_i))`

. I know how to optimize neural networks, but I have no idea how to apply Adam for this function.

How to create such a model? Could you please help?