In this paper, we present an online identification method to the problem of parameter estimation from binary observations. A recursive identification algorithm with low-storage requirements and computational complexity is derived. We prove the convergence of this method provided that the input signal satisfies a strong mixing property. Some simulation results are then given in order to illustrate the properties of this method under various scenarios. This method is appealing in the context of microelectronic devices since it only requires a 1-bit analog-to-digital converter, with low power consumption and minimal silicon area. (c) 2012 Elsevier Ltd. All rights reserved.