Application of higher order spectral analysis to cubicallynonlinear system identification
IEEE Transactions on Signal Processing
Second-order Volterra system identification
IEEE Transactions on Signal Processing
A fast recursive least squares adaptive second order Volterrafilter and its performance analysis
IEEE Transactions on Signal Processing
Extended generalized total least squares method for theidentification of bilinear systems
IEEE Transactions on Signal Processing
Identification of structurally constrained second-order Volterramodels
IEEE Transactions on Signal Processing
Nonlinear system identification using Gaussian inputs
IEEE Transactions on Signal Processing
Identification of input-output bilinear systems using cumulants
IEEE Transactions on Signal Processing
Asymptotic theory of mixed time averages and kth-order cyclic-moment and cumulant statistics
IEEE Transactions on Information Theory
Hi-index | 22.14 |
The identification of a special class of polynomial models is pursued in this paper. In particular a parameter estimation algorithm is developed for the identification of an input-output quadratic model excited by a zero mean white Gaussian input and with the output corrupted by additive measurement noise. Input-output crosscumulants up to the fifth order are employed and the identification problem of the unknown model parameters is reduced to the solution of successive triangular linear systems of equations that are solved at each step of the algorithm. Simulation studies are carried out and the proposed methodology is compared with two least squares type identification algorithms, the output error method and a combination of the instrumental variables and the output error approach. The proposed cumulant based algorithm and the output error method are tested with real data produced by a robotic manipulator.