Clustering Input Signals Based Identification Algorithms for Two-Input Single-Output Models with Autoregressive Moving Average Noises

Table 3

The parameter estimates and their errors with clustering inputs based recursive least squares algorithm .

100	−1.95143	0.95564	0.02088	0.00902	−0.00756	−0.01860	0.85720	4.09050
150	−1.93967	0.94270	0.00767	0.00885	0.00027	−0.01209	0.85790	3.63789
200	−1.93795	0.94031	0.00674	0.00148	−0.00322	0.00090	0.88401	4.54653
500	−1.93131	0.93401	0.01091	−0.00665	0.00016	0.00787	0.77077	1.31455
1000	−1.92317	0.92560	0.00940	−0.00678	0.00352	0.00169	0.79810	0.74356
2000	−1.92398	0.92599	0.01380	−0.01034	0.00362	−0.00244	0.79445	0.67360
3000	−1.92460	0.92681	0.01361	−0.01012	0.00163	−0.00070	0.79356	0.66986
True values	−1.91500	0.91740	0.01118	−0.01059	0.00021	0.00020	0.78720