The implementation of high‑throughput systems with the traditional approach to the discretization of the analog signal according to the Kotelnikov theorem is faced with the problems of high power consumption and the need to store and transfer large amounts of data. An alternative approach to sampling and processing information is based on advances in the compressed sampling theory. The paper provides a brief overview of the main provisions of this theory and considers examples of its use in practice for the implementation of information reading systems – analog‑to‑information converters. The purpose of these devices is to reduce the pressure on conventional analog‑to‑digital converters, to reduce the sampling rate and the amount of output data. The main architectures of analog‑information converters are considered: non‑uniform sampling, random filter, random demodulator, modulated wideband converter, compressive multiplexer, random modulator pre‑integrator, spread spectrum random modulator pre‑integrator.