Sentence examples for more state variables from inspiring English sources

Many models of physiological processes have the feature that one or more state variables evolve much faster than the other variables.

The mathematical analysis for the phase-type probability distributions of both UST and CDT can be developed in a similar way, considering more state variables.

The vehicle model is built on Simulink with S-function blocks (Fig. 8), which allow to extract more state variables of studied system for estimation, observation or control purpose.

They exhibit many of the features that make the design and verification of CPS so difficult: hybrid dynamics, large continuous dynamics in each mode (e.g., 10 or more state variables), and nontrivial specifications involving nonlinear constraints on the state variables.

There are more state variables than the reduced-order models, owing to the complicated model construction, such as the pitch angle θ p, the generator rotor speed ω g, the wind turbine shaft speed ω wt, and q-axis subtransient electromotive force E q ″.

The main conclusion in the paper is that due to the low computation time, the convex modeling approach enables optimization of problems with two or more state variables, e.g. allowing for thermal models of the components; or to include more sizing variables, e.g. sizing of the engine and the electric machine simultaneously.

Hyperchaotic systems can be obtained by adding one more state variable to a three-dimensional chaotic system [33].

A glitch that occurs as a result of two or more state variable changes during a state-to-state transition is called an output race glitch or simply ORG.

More weak connections: With more than two state variables, it becomes possible that E k is connected with X l for some l

Here we simulate a decision-switch model of gene regulation with more than two state variables and with time-varying repression among regulatory factors.

More than two state variables: With a number of state variables n, the square in the proof will become a hypercube in n dimensions, with 2 n corners, each corner representing a possible previous sequence of estimates of each of the n state variables.