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

Table 4

The parameter estimates and their errors with recursive extended least squares algorithm ().

100	−1.97147	0.97335	0.05353	0.00627	−0.04936	−0.06507	0.92321	8.09537
150	−1.96166	0.96353	0.05168	0.00369	−0.02666	−0.06936	0.91879	7.52280
200	−1.95621	0.95814	0.03615	0.00566	−0.05065	−0.05989	0.92000	7.39901
500	−1.94218	0.94465	0.00382	−0.01273	−0.02587	−0.02403	0.78074	2.35679
1000	−1.93122	0.93353	0.00419	−0.01047	−0.01735	−0.02436	0.80766	1.92573
2000	−1.92860	0.93052	-0.00021	−0.01672	0.00250	0.00642	0.79432	1.09858
3000	−1.92823	0.93035	0.00055	−0.01889	−0.00086	0.00758	0.79205	1.08487
True values	−1.91500	0.91740	0.01118	−0.01059	0.00021	0.00020	0.78720