Title : 
A recursive system identification method based on binary measurements
         
        
            Author : 
Jafari, Kian ; Juillard, Jerome ; Colinet, Eric
         
        
            Author_Institution : 
Dept. of Signal Process. & Electron. Syst., SUPELEC, Gif-sur-Yvette, France
         
        
        
        
        
        
            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.
         
        
            Keywords : 
FIR filters; least mean squares methods; recursive estimation; binary measurement; finite-impulse response system; least mean squares method; parameter estimation; recursive system identification method; Built-in self-test; Context; Convergence; Estimation; Least squares approximation; Noise; Parameter estimation;
         
        
        
        
            Conference_Titel : 
Decision and Control (CDC), 2010 49th IEEE Conference on
         
        
            Conference_Location : 
Atlanta, GA
         
        
        
            Print_ISBN : 
978-1-4244-7745-6
         
        
        
            DOI : 
10.1109/CDC.2010.5717798