Recursive identification of IIR system using binary input/output measurements

Abstract

The identification of system using binary measurements of both the input and output is a problem relevant to a number of applications. Although the identification of finite impulse response (FIR) models has been thorough, more complex model structures still need to be investigated. In this paper, the problem of identifying an infinite impulse response (IIR) system is studied. A three-step real-time algorithm is proposed. The proposed algorithm is based on the use of least mean squares (LMS) algorithm to estimate the correlation function, then estimate the parameters of the system. A convergence analysis of the proposed algorithm based on those of LMS algorithm is presented. Some simulation results are included to illustrate the performance of the proposed algorithm.