Pages that link to "Item:Q1660694"

The following pages link to Parameter identification of a class of nonlinear systems based on the multi-innovation identification theory (Q1660694):

Displaying 19 items.

• A novel parameter separation based identification algorithm for Hammerstein systems (Q289245) (← links)
• Recursive parameter estimation algorithms and convergence for a class of nonlinear systems with colored noise (Q318193) (← links)
• Data filtering based forgetting factor stochastic gradient algorithm for Hammerstein systems with saturation and preload nonlinearities (Q325722) (← links)
• Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering (Q508335) (← links)
• New gradient based identification methods for multivariate pseudo-linear systems using the multi-innovation and the data filtering (Q508358) (← links)
• Design of multi innovation fractional LMS algorithm for parameter estimation of input nonlinear control autoregressive systems (Q823450) (← links)
• An intelligent parameter varying (IPV) approach for nonlinear system identification of base excited structures (Q873366) (← links)
• Adaptive gradient-based iterative algorithm for multivariable controlled autoregressive moving average systems using the data filtering technique (Q1654319) (← links)
• The maximum likelihood least squares based iterative estimation algorithm for bilinear systems with autoregressive moving average noise (Q2011872) (← links)
• Parameter identification of systems with preload nonlinearities based on the finite impulse response model and negative gradient search (Q2017916) (← links)
• Hierarchical stochastic gradient algorithm and its performance analysis for a class of bilinear-in-parameter systems (Q2400914) (← links)
• Recursive least squares algorithm for nonlinear dual-rate systems using missing-output estimation model (Q2400915) (← links)
• Gradient-based recursive identification methods for input nonlinear equation error closed-loop systems (Q2402054) (← links)
• Modelling and multi-innovation parameter identification for Hammerstein nonlinear state space systems using the filtering technique (Q2808783) (← links)
• (Q3462958) (← links)
• (Q3647940) (← links)
• Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion (Q6053746) (← links)
• Identification of the nonlinear systems based on the kernel functions (Q6071550) (← links)
• Data filtering‐based parameter estimation algorithms for a class of nonlinear systems with colored noises (Q6081010) (← links)