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

Table 5

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

100	−1.95228	0.95651	0.04939	0.06757	−0.03077	−0.07524	0.85825	6.57724
150	−1.94032	0.94335	−0.00357	0.06691	0.00048	−0.04913	0.85867	5.42231
200	−1.93854	0.94091	−0.00706	0.03772	−0.01351	0.00282	0.88457	5.12093
500	−1.93184	0.93455	0.00972	0.00515	0.00004	0.03079	0.77074	1.99164
1000	−1.92349	0.92592	0.00389	0.00459	0.01344	0.00614	0.79809	1.21529
2000	−1.92412	0.92613	0.02165	−0.00941	0.01386	−0.01036	0.79444	1.10021
3000	−1.92474	0.92695	0.02079	−0.00858	0.00593	−0.00340	0.79351	0.84690
True values	−1.91500	0.91740	0.01118	−0.01059	0.00021	0.00020	0.78720