Pages that link to "Item:Q2847892"

The following pages link to Nonlinear system identification. NARMAX methods in the time, frequency, and spatio-temporal domains (Q2847892):

Displaying 50 items.

• A comparative and experimental study on gradient and genetic optimization algorithms for parameter identification of linear MIMO models of a drilling vessel (Q327032) (← links)
• A randomized algorithm for nonlinear model structure selection (Q900226) (← links)
• Stability orthogonal regression for system identification (Q1645072) (← links)
• Computation of the largest positive Lyapunov exponent using rounding mode and recursive least square algorithm (Q1663919) (← links)
• Forecasting and uncertainty quantification using a hybrid of mechanistic and non-mechanistic models for an age-structured population model (Q1670479) (← links)
• On the analysis of pseudo-orbits of continuous chaotic nonlinear systems simulated using discretization schemes in a digital computer (Q1674277) (← links)
• Identification of block-oriented nonlinear systems starting from linear approximations: a survey (Q1679865) (← links)
• Data-based stochastic model reduction for the Kuramoto-Sivashinsky equation (Q1686773) (← links)
• Tracking nonlinear correlation for complex dynamic systems using a windowed error reduction ratio method (Q1687461) (← links)
• On the use of interval extensions to estimate the largest Lyapunov exponent from chaotic data (Q1721305) (← links)
• Ranking the importance of variables in nonlinear system identification (Q1737872) (← links)
• WH-EA: an evolutionary algorithm for Wiener-Hammerstein system identification (Q1784336) (← links)
• Control of complex nonlinear dynamic rational systems (Q1785190) (← links)
• Recursive nonlinear-system identification using latent variables (Q1797027) (← links)
• The effects of linear and nonlinear characteristic parameters on the output frequency responses of nonlinear systems: the associated output frequency response function (Q1797043) (← links)
• The analysis of nonlinear systems in the frequency domain using nonlinear output frequency response functions (Q1797151) (← links)
• A new GUI interpretation tool for the nonlinear frequency response function (Q1867786) (← links)
• Improved discrete techniques of time-delay and order estimation for large-scale interconnected nonlinear systems (Q1992430) (← links)
• Fault detection strategy combining NARMAX model and Bhattacharyya distance for process monitoring (Q1996655) (← links)
• Memory-based reduced modelling and data-based estimation of opinion spreading (Q2022637) (← links)
• Koopman operator framework for time series modeling and analysis (Q2022703) (← links)
• Identification of Wiener-Hammerstein models based on variational Bayesian approach in the presence of process noise (Q2041405) (← links)
• Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories (Q2050562) (← links)
• Design of fractional hierarchical gradient descent algorithm for parameter estimation of nonlinear control autoregressive systems (Q2098687) (← links)
• Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism (Q2123923) (← links)
• System identification through Lipschitz regularized deep neural networks (Q2132640) (← links)
• The estimation method of normalized nonlinear output frequency response functions with only response signals under stochastic excitation (Q2137339) (← links)
• Resilient fault-tolerant anti-synchronization for stochastic delayed reaction-diffusion neural networks with semi-Markov jump parameters (Q2185773) (← links)
• One-shot set-membership identification of generalized Hammerstein-Wiener systems (Q2188270) (← links)
• A robust model structure selection method for small sample size and multiple datasets problems (Q2195372) (← links)
• \(U\)-model and \(U\)-control methodology for nonlinear dynamic systems (Q2205226) (← links)
• Algorithms for U-model-based dynamic inversion (UM-dynamic inversion) for continuous time control systems (Q2205274) (← links)
• Identification of stochastic nonlinear models using optimal estimating functions (Q2207186) (← links)
• A tree adjoining grammar representation for models of stochastic dynamical systems (Q2207237) (← links)
• Nonlinear system identification with regularized tensor network B-splines (Q2208614) (← links)
• Deep learning of dynamics and signal-noise decomposition with time-stepping constraints (Q2222431) (← links)
• Non-fragile dissipative state estimation for semi-Markov jump inertial neural networks with reaction-diffusion (Q2245940) (← links)
• Linear prediction error methods for stochastic nonlinear models (Q2280666) (← links)
• A new convergence analysis for the Volterra series representation of nonlinear systems (Q2288602) (← links)
• Identification of distributed-parameter systems from sparse measurements (Q2294789) (← links)
• A randomized two-stage iterative method for switched nonlinear systems identification (Q2304051) (← links)
• Identification of the dynamic parametrical model with an iterative orthogonal forward regression algorithm (Q2307042) (← links)
• Detecting unreliable computer simulations of recursive functions with interval extensions (Q2318236) (← links)
• Parametric identification of parallel Wiener-Hammerstein systems (Q2342520) (← links)
• A sliding-window approximation-based fractional adaptive strategy for Hammerstein nonlinear ARMAX systems (Q2407814) (← links)
• Structure discrimination in block-oriented models using linear approximations: a theoretic framework (Q2409436) (← links)
• Model structure selection for switched NARX system identification: a randomized approach (Q2663909) (← links)
• Non-parametric identification of homogeneous dynamical systems (Q2665098) (← links)
• Forecasting of nonlinear dynamics based on symbolic invariance (Q2701225) (← links)
• Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models (Q2792948) (← links)