A Recursive System Identification Method Based on Binary Measurements

Abstract : An online approach to parameter estimation problems based on binary observations is presented in this paper. This recursive identification method relies on a least-mean squares approach which makes it possible to estimate the coefficients of a finite-impulse response system knowing only the system input and the sign of the system output. The impulse response is identified up to a positive multiplicative constant. The role of the regulative coefficient is investigated thanks to simulated data. The proposed method is compared with another online approach: it is shown that the proposed method is competitive with the other one in terms of estimation quality and of calculation complexity.
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Kian Jafaridinani, Jérôme Juillard, Eric Colinet. A Recursive System Identification Method Based on Binary Measurements. 49th IEEE Conference on Decision and Control (CDC'10), Dec 2010, Atlanta, United States. pp.1167-1171. ⟨hal-00551800⟩

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