How to calculate gradient of output of a neural network with respect to its parameters?

utkarsh_singh_021 asked: 2021-05-04 deep learning , matlab , simulink ,

Learn how to calculate the gradient of a neural networks output with respect to its parameters in MATLAB. This resource provides clear steps and examples. Get

Expert Answer

Neeta Dsouza answered . 2025-07-30 20:03:27

You can use dlgradient and dlfeval to take derivatives with respect to the input or to the parameters

Here's an example:

I'm going to let this function play the role of the neural network. You should use dlnetwork to create a more complex network.

function y = f(x,theta)
y = sum(sin(theta(1)*x+theta(2)));
end

Then I need to scope the computation of the function so that dlfeval knows where to apply auto-diff. I do that by defining a function that evaluates the network and computes the gradient of interest. In this case:

function [y, dy] = fun_and_deriv(x,theta)
y = f(x,theta);
dy = dlgradient(y,theta);
end

Then I can compute the derivative:

x = dlarray(0:10);
theta = dlarray([1 2]);
[y, dy] = dlfeval(@fun_and_deriv,x,theta)

which gives:

y = 
  1×1 dlarray

   -0.9668

dy = 
  1×2 dlarray

    0.6788   -1.1095

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