Hello Lup,
I understand that you are trying to implement a custom loss function for your neural network in MATLAB, where the loss is calculated by multiplying the output of the network by the input vector and then computing the mean squared error between this result and some memory vectors that were not passed to the network.
To implement a custom loss function, you need to create a function that calculates the loss according to your specific requirements. This function takes the predictions from the network, the memory vectors, and the original input vector as arguments. Inside this function, perform the multiplication of the network's output coefficients with the input vector, and then compute the MSE between this product and the memory vectors.
You can pass the custom loss function as a function handle into the "lossFcn" parameter in the "trainNetwork" function.
Please refer to the below documentation to learn more about the loss function in the "trainNetwork" function.
Please refer to the below documentation on how to define custom operations as MATLAB functions for Deep Learning Operations.
I hope this helps.
