Sentence examples for fractional transformation from inspiring English sources

In the first step a neural state-space model is transformed into a linear fractional transformation (LFT) representation to obtain a discrete-time quasi-LPV model of a nonlinear plant from input-output data only.

Here a discrete-time polytopic quasi linear parameter varying (LPV) model of a nonlinear system based on a neural state-space model is proposed, whereas in the joint paper (Abbas and Werner [2008]) a neural state-space model is transformed into a linear fractional transformation (LFT) representation to obtain a discrete-time quasi-LPV model of the nonlinear system.

Here a neural state-space model is transformed into a linear fractional transformation (LFT) representation to obtain a discrete-time quasi-linear parameter-varying (LPV) model of a nonlinear plant, whereas in the joint paper (Abbas and Werner [2008]) a method is proposed to transform the neural state-space into a discrete-time polytopic quasi-LPV model.

Furthermore, the unscented transform (UT) and the linear fractional transformation (LFT) are combined with the closed-form solution for the nonlinear jump Markov multi-target models in [23, 24].

The uncertainty is described in linear fractional transformation (LFT) form.

This representation of the compact set of models makes use of the Linear Fractional Transformation.

(9/11-9/13) Conformapsmand and linear fractional transformations.

Two sets of finite-dimensional strongly stabilizing controllers are parameterized in terms of linear fractional transformations.

The second approach concerns interpolation theory with linear fractional transformations and the tangential Schur algorithm.

After establishing the closure of such systems under linear fractional transformations, we formulate the H2 optimal control problem using the model-matching framework.

Two alternatives are discussed, leading to representations which are linear fractional transformations with matrix coefficients acting on infinite Hessenberg or five-diagonal unitary matrices.