it down differently you can just write it down as a Fourier operation and then effectively a mask which defines how you're under sampled case space and that's that's quite important okay so in what you're trying to then solve mathematically is typically an unconstrained optimization problem consisting of your regularization term if you would use compressed sensing you'd probably use here an l1 or LZ row prior a norm or and the data fidelity term and that data fidelity term is quite crucial and it's actually something which is not so easy to bring