I am implementing some head tracking and I get 2 matrices of horizontal velocities. (A vector field decomposed into vertical and horizontal velocities). For each of these matrices I do some math to calculate the actual head tracking.
My question is, is there a way to do that math (which is a set of blocks) on both matrices without copying the math blocks onto each signal?
It’s hard to explain so here’s a screen shot of my model:
You can see that the "complex to real-imag" block has 2 outputs (this is the little one in the middle). The mean block and the integrator circuit then calculate the head velocity and position for the real matrix (horizontal position). I want to do exactly the same routine on the imaginary matrix (vertical direction). Obviously I can just copy the blocks, but surely there must be a better way of doing it? In a way I’m looking for an analogue of a loop in "normal programming" like C or something, where a block of code is executed several times on different inputs.
One way to easily reuse a set of blocks is to create a subsystem out of them. In your case, you can create a subsystem by grouping existing blocks, then simply copy and paste your subsystem to use it for your imaginary output.
Although potentially more complicated, you could also look into using mux signals to avoid having to copy parts of your model.