1. What have the authors contributed in "A recursive system identification method based on binary measurements" ?
An online approach to parameter estimation problems based on binary observations is presented in this paper.
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A recursive system identification method based on binary measurements
Kian Jafari,Jerome Juillard,Eric Colinet +2 more
- 01 Dec 2010
- pp 1154-1158
TL;DR: An online approach to parameter estimation problems based on binary observations is presented and 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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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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Citations
Consensus of Multi-Agent Systems Under Binary-Valued Measurements and Recursive Projection Algorithm
TL;DR: It is proved that the estimates of the states can converge to the true states with a faster convergence rate than that in the parameter estimation.
60
Convergence analysis of an online approach to parameter estimation problems based on binary observations
TL;DR: An online identification method to the problem of parameter estimation from binary observations with low-storage requirements and computational complexity is derived and it is proved the convergence of this method provided that the input signal satisfies a strong mixing property.
51
Asymptotically Efficient Recursive Identification of FIR Systems With Binary-Valued Observations
TL;DR: This paper considers the identification problem of finite impulse response (FIR) systems with binary-valued observations under the assumption of fixed threshold and bounded persistently excitations and shows that the proposed recursive projection algorithm is optimal in the sense of asymptotic efficiency.
31
Identification Using Binary Measurements for IIR Systems
TL;DR: The key to the approach is to recast the initial identification problem into an identification problem in the set-membership framework, which enables the system to be identified using an identification algorithm devoted to IIR systems in such a framework.
30
Convergence analysis of an online approach to parameter estimation problems based on binary noisy observations
Laurent Bourgois,Jerome Juillard +1 more
- 01 Dec 2012
TL;DR: The convergence analysis of an online system identification method based on binary-quantized observations is presented and a lower bound of the correlation coefficient between the nominal and the estimated system parameters is found.
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System identification using binary sensors
TL;DR: System identification is investigated for plants that are equipped with only binary-valued sensors, revealing that binary sensors impose fundamental limitations on identification accuracy and time complexity, and carry distinct features beyond identification with regular sensors.