In this paper we consider the problem of retrieving information from a set of noisy and distorted measurements. More precisely we consider a scenario where a set of trajectories x1(t),...,xn(t) are observed using a single measuring device so that the output y(ti) of the device at each sampling point is an observation of precisely one of x1(t),...,xn(t). The process can be modeled as a discrete switched system. We develop a recursive Classification, Correction and Identification Algorithm (CCIA), that recovers xj(ti) and the switching parameter δj(ti) together with the ratio zj of measurements from each state xj(ti).