As per topic. Is there any well established method for solving linear systems for binary data? pardon if this is in wrong cathegory, english is not my first language and I'm not that well aware of the english terms. i.e. the classical g = M*f problem, where g is measured data and we want to know f. In this case, with calibration data we can determine M, but it has an ill-conditioned inverse, so the classical solution of f = M-1*g doesn't work. Enter the Tikhonov regularization, but it fails to be accurate enough. Conjugate gradient method, i.e. solving min || M*f-g|| might work, if the M was positive definite, but it is not. (it's symmetrical though). Also, we demand that every element of f and g is either 0 or 1, as the measured data g is in binary form. Google scholar was of little help, so... so in short a) Is there any well know tools for the problem when the data is binaric b) am I screwed?