Research Article
Filtering Based Recursive Least Squares Algorithm for Multi-Input Multioutput Hammerstein Models
Table 1
The F-MRLS estimates and errors in Example
1 (
and
).
| | | | | | | | | (%) |
| | 100 | 0.10919 | −1.60279 | 0.39771 | 0.12515 | −0.16795 | 0.46319 | 33.14292 | 200 | 0.08155 | −1.44298 | 0.31145 | 0.09590 | −0.13875 | 0.51078 | 21.01533 | 500 | 0.10144 | −1.33934 | 0.25923 | 0.08705 | −0.15442 | 0.60335 | 11.18663 | 1000 | 0.12452 | −1.30385 | 0.26703 | 0.11599 | −0.14796 | 0.65282 | 7.04142 | 2000 | 0.13930 | −1.27241 | 0.26711 | 0.12703 | −0.14550 | 0.69136 | 4.66378 | 3000 | 0.14008 | −1.25781 | 0.26567 | 0.11928 | −0.14361 | 0.70371 | 4.03373 |
| | 100 | 0.09530 | −1.72159 | 0.52726 | 0.13387 | −0.15869 | 0.52551 | 42.21841 | 200 | 0.03631 | −1.52223 | 0.36553 | 0.07113 | −0.11792 | 0.58022 | 25.56872 | 500 | 0.07400 | −1.40400 | 0.25492 | 0.04715 | −0.16037 | 0.64763 | 15.50868 | 1000 | 0.12015 | −1.36311 | 0.27803 | 0.10606 | −0.15335 | 0.68001 | 11.08080 | 2000 | 0.14849 | −1.31457 | 0.28056 | 0.12704 | −0.15048 | 0.70624 | 7.98334 | 3000 | 0.15005 | −1.29138 | 0.27909 | 0.10998 | −0.14680 | 0.71335 | 6.79480 |
| True values | 0.13000 | −1.21000 | 0.25000 | 0.13000 | −0.14000 | 0.68000 | |
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