Pages that link to "Item:Q2435673"
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The following pages link to Filtering based recursive least squares algorithm for Hammerstein FIR-MA systems (Q2435673):
Displaying 17 items.
- Hierarchical least squares algorithms for nonlinear feedback system modeling (Q328119) (← links)
- Recursive least squares algorithm and gradient algorithm for Hammerstein-Wiener systems using the data filtering (Q332822) (← links)
- Decomposition-based recursive least squares algorithm for Wiener nonlinear feedback FIR-MA systems using the filtering theory (Q736331) (← links)
- Orthotopic-filtering-based fault diagnosis algorithms for nonlinear systems with slowly varying faults (Q776146) (← links)
- Stochastic gradient algorithm for multi-input multi-output Hammerstein FIR-MA-like systems using the data filtering (Q1660400) (← links)
- Least squares based and two-stage least squares based iterative estimation algorithms for H-FIR-MA systems (Q1665895) (← links)
- Filtering based recursive least squares algorithm for multi-input multioutput Hammerstein models (Q1717904) (← links)
- Newton iterative identification method for an input nonlinear finite impulse response system with moving average noise using the key variables separation technique (Q2259602) (← links)
- Filtering based multi-innovation extended stochastic gradient algorithm for Hammerstein nonlinear system modeling (Q2282624) (← links)
- Several gradient-based iterative estimation algorithms for a class of nonlinear systems using the filtering technique (Q2346248) (← links)
- Decentralized adaptive neural network control for mechanical systems with dead-zone input (Q2348208) (← links)
- Hierarchical recursive least squares algorithm for Hammerstein systems using the filtering method (Q2353884) (← links)
- A sliding-window approximation-based fractional adaptive strategy for Hammerstein nonlinear ARMAX systems (Q2407814) (← links)
- Maximum likelihood Newton recursive and the Newton iterative estimation algorithms for Hammerstein CARAR systems (Q2436166) (← links)
- Data filtering based recursive least squares algorithm for Hammerstein systems using the key-term separation principle (Q2510471) (← links)
- Least squares based iterative identification algorithms for input nonlinear controlled autoregressive systems based on the auxiliary model (Q2517579) (← links)
- An evolving concept in the identification of an interval fuzzy model of Wiener-Hammerstein nonlinear dynamic systems (Q6139443) (← links)
