Sentence examples for models the unknown from inspiring English sources

For the classic optimal control problem, GPDP models the unknown value functions with Gaussian processes and generalizes dynamic programming to continuous-valued states and actions.

We discuss here the existence and the computation of a robust controller set for uncertain systems that can be described by parametric models, the unknown parameters of which are assumed to vary between known bounds.

In this case, the process noise wk−1 models the unknown movements along x and y axes.

J. Meng et al. propose a novel Bayesian sparse-correlated rectified factor model (BSCRFM) that models the unknown transcription factor (TF) protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes.

A novel Bayesian sparse correlated rectified factor model (BSCRFM) is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes.

In the second step, the variants are evaluated using rigorous models, wherein the unknown model parameters are varied to quantify their influence on the process performance.

The Smagorinsky model formulation is used to model the unknown turbulent stresses.

A new dynamic neural network structure is utilised to model the unknown plant dynamics through modelling the input-output mapping.

In the model, the unknown source amplitudes of the virtual sources are adaptively estimated by using Kalman filters (KFs).

By designing the state observer, the adaptive fuzzy systems, which are used to model the unknown functions, can be constructed using the state estimations.

The fuzzy logic systems are used to model the unknown nonlinear system, and a fuzzy state observer is designed to estimate the immeasurable states.