Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...
This paper addresses robust deconvolution filtering when the system and noise dynamics are obtained by parametric system identification. Consistent with standard identification me...
Least-squares estimation has always been the main approach when applying prediction error methods (PEM) in the identification of linear dynamical systems. Regardless of the estim...
We consider a mixed linear system model, with both continuous and discrete inputs and outputs, described by a coefficient matrix and a set of noise variances. When the discrete inp...
Argyrios Zymnis, Stephen P. Boyd, Dimitry M. Gorin...
This paper describes a new kernel-based approach for linear system identification of stable systems. We model the impulse response as the realization of a Gaussian process whose s...