linear combination of each of these layers here the input is the volume of shape DG cross DG cross M the filter K PC has a shape one cross one cross M this is basically a 1 Cross 1 convolution operation over all M layers the output will thus have the same input width and height as the input D G cross DG for each filter assuming that we want to use some n such filters the output volume becomes D G cross DG cross n so that's great we got this down now let's take a look at the complexity of this convolution we can split this into two