FIR System Identification Using Feedback

T. J. Moir
2013 Journal of Signal and Information Processing  
This paper describes a new approach to finite-impulse (FIR) system identification. The method differs from the traditional stochastic approximation method as used in the traditional least-mean squares (LMS) family of algorithms, in which we use deconvolution as a means of separating the impulse-response from the system input data. The technique can be used as a substitute for ordinary LMS but it has the added advantages that can be used for constant input data (i.e. data which are not
more » ... h are not persistently exciting) and the stability limit is far simpler to calculate. Furthermore, the convergence properties are much faster than LMS under certain types of noise input.
doi:10.4236/jsip.2013.44049 fatcat:prukimcvxfai5mueoemnyncfga