Sentence examples for approximation behavior from inspiring English sources
By now, the approximation behavior of the Baskakov-Durrmeyer operator is well understood.
In the literature, many authors have discussed the approximation behavior of different summation-integral type operators (see [5, 6]).
We provide theoretical analysis of the approximation behavior and also design convergence guaranteed numerical algorithms based on Bregman iteration.
Automatic adaptive mesh-refining algorithms are an important tool to improve the approximation behavior of the finite element discretization.
Optimal approximation behavior is observed numerically, and examples of applications to free-form design, smooth hole-filling, and high-order partial differential equations demonstrate the applicability of the developed framework.
The other results are the quantitative form of Voronovskaya type results which present a new aspect to the pointwise approximation behavior of corresponding operators that we can use to investigate; the rate of pointwise convergence and an upper bound for the error of this pointwise approximation are presented simultaneously.
Several authors have proposed theq analogues of Kantorovich-type modification of different linearpositive operators and studied their statistical approximation behaviors.
The concern of this paper is to introduce a Kantorovich modification of (( p,q ) )-Baskakov operators and investigate their approximation behaviors.
Furthermore, we can not ignore the fact that brain processing mechanisms in the modification of emotions and behaviors, such as the activation of the left frontal pole related to positive thoughts and approximation behaviors, and the activation of the right frontal pole which is related to negative thoughts and avoidance behaviors.
In order to visualize the approximation error behavior of the proposed methods with different N, we plot the speed of the errors damping under different coefficients in Figures 2 and 3.
17 Agent rules also offer a means of introducing stochasticity through probabilistic events, allowing for an approximation of behaviors in nondeterministic systems.
