Pages that link to "Item:Q6099494"

The following pages link to Separable synthesis gradient estimation methods and convergence analysis for multivariable systems (Q6099494):

Displaying 35 items.

• Gradient estimation for discrete-event systems by measure-valued differentiation (Q4635145) (← links)
• Separable multi‐innovation stochastic gradient estimation algorithm for the nonlinear dynamic responses of systems (Q5003429) (← links)
• A novel predefined-time noise-tolerant zeroing neural network for solving time-varying generalized linear matrix equations (Q6082822) (← links)
• Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data (Q6099491) (← links)
• The data-filtering based bias compensation recursive least squares identification for multi-input single-output systems with colored noises (Q6099840) (← links)
• Distributed online multi‐task sparse identification for multiple systems with asynchronous updates (Q6117510) (← links)
• Parameter estimation of multivariable Wiener nonlinear systems by the improved particle swarm optimization and coupling identification (Q6126875) (← links)
• Iterative parameter identification algorithms for transformed dynamic rational fraction input-output systems (Q6133112) (← links)
• Parameter estimation of multiple‐input single‐output Hammerstein controlled autoregressive system based on improved adaptive moment estimation algorithm (Q6154590) (← links)
• Maximum likelihood interval-varying recursive least squares identification for output-error autoregressive systems with scarce measurements (Q6168998) (← links)
• Filtering-based gradient joint identification algorithms for nonlinear fractional-order models with colored noises (Q6183845) (← links)
• Filtered auxiliary model recursive generalized extended parameter estimation methods for Box–Jenkins systems by means of the filtering identification idea (Q6193184) (← links)
• Multi‐innovation gradient‐based iterative identification methods for feedback nonlinear systems by using the decomposition technique (Q6194657) (← links)
• Highly‐computational hierarchical iterative identification methods for multiple‐input multiple‐output systems by using the auxiliary models (Q6194874) (← links)
• Parameter and order estimation algorithms and convergence analysis for lithium‐ion batteries (Q6197896) (← links)
• Auxiliary model-based hierarchical stochastic gradient methods for multiple-input multiple-output systems (Q6489227) (← links)
• Decomposition and composition modeling algorithms for control systems with colored noises (Q6498049) (← links)
• A filtering-based recursive extended least squares algorithm and its convergence for finite impulse response moving average systems (Q6545340) (← links)
• A coupled recursive least squares algorithm for multivariable systems and its computational amount analysis by using the coupling identification concept (Q6558256) (← links)
• Q-learning based adaptive Kalman filtering for partial model-free dynamic systems (Q6558278) (← links)
• Hierarchical estimation methods based on the penalty term for controlled autoregressive systems with colored noises (Q6560443) (← links)
• Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises (Q6569390) (← links)
• Novel parameter estimation method for the systems with colored noises by using the filtering identification idea (Q6569400) (← links)
• Distributed identification based partially-coupled recursive generalized extended least squares algorithm for multivariate input-output-error systems with colored noises from observation data (Q6572457) (← links)
• Cauchy kernel correntropy-based robust multi-innovation identification method for the nonlinear exponential autoregressive model in non-Gaussian environment (Q6577233) (← links)
• Decomposition-based maximum likelihood gradient iterative algorithm for multivariate systems with colored noise (Q6577238) (← links)
• Dynamic observer-based fault estimation and fault-tolerant control for switched stochastic systems with multiple faults (Q6583403) (← links)
• Filtered generalized iterative parameter identification for equation-error autoregressive models based on the filtering identification idea (Q6585579) (← links)
• Identification of linear systems using binary sensors with random thresholds (Q6595002) (← links)
• Multiple-model state-space system identification with time delay using the EM algorithm (Q6611346) (← links)
• A modified gradient-based iterative algorithm for solving the complex conjugate and transpose matrix equations (Q6619381) (← links)
• Auxiliary model maximum likelihood gradient-based iterative identification for feedback nonlinear systems (Q6631782) (← links)
• Hierarchical gradient-based iterative parameter estimation algorithms for a nonlinear feedback system based on the hierarchical identification principle (Q6652739) (← links)
• Adaptive multi-innovation gradient identification algorithms for a controlled autoregressive moving average model (Q6652767) (← links)
• Sliding window iterative identification for nonlinear closed-loop systems based on the maximum likelihood principle (Q6664769) (← links)