Convergence Analysis of an online Approach to Parameter Estimation Problems Based on Binary Observations

Abstract : 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 micro-electronic devices since it only requires a 1-bit analog-to-digital converter, with low power consumption and minimal silicon area.
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Kian Jafaridinani, Jérome Juillard, Morgan Roger. Convergence Analysis of an online Approach to Parameter Estimation Problems Based on Binary Observations. Automatica, Elsevier, 2012, 48 (11), pp.2837-2842. ⟨10.1016/j.automatica.2012.05.050⟩. ⟨hal-00747809⟩

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