Pages that link to "Item:Q1660514"
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The following pages link to Iterative identification methods for input nonlinear multivariable systems using the key-term separation principle (Q1660514):
Displaying 14 items.
- Hierarchical parameter estimation for a class of MIMO Hammerstein systems based on the reframed models (Q253892) (← links)
- Least squares identification for Hammerstein multi-input multi-output systems based on the key-term separation technique (Q318219) (← links)
- Hierarchical multi-innovation extended stochastic gradient algorithms for input nonlinear multivariable OEMA systems by the key-term separation principle (Q341679) (← links)
- Hierarchical Newton iterative parameter estimation of a class of input nonlinear systems based on the key term separation principle (Q1723012) (← links)
- Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation (Q2030993) (← 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)
- Parameter estimation algorithms for multivariable Hammerstein CARMA systems (Q2279538) (← links)
- Filtering-based multistage recursive identification algorithm for an input nonlinear output-error autoregressive system by using the key term separation technique (Q2399050) (← links)
- Iterative estimation methods for Hammerstein controlled autoregressive moving average systems based on the key-term separation principle (Q2439375) (← links)
- Identification of systems with hard input nonlinearities (Q2758344) (← links)
- Adaptive filtering scheme for parameter identification of nonlinear Wiener–Hammerstein systems and its application (Q5130073) (← links)
- Modelling and identification of nonlinear cascade systems with backlash input and static output nonlinearities (Q5861070) (← links)
- Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion (Q6053746) (← links)
- Learning low-dimensional separable decompositions of MIMO non-linear systems (Q6105538) (← links)
