uniform approximation
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Author(s):  
Truman Tapia ◽  
Clara Rojas

In this work, we calculate the tensor power spectrum and the tensor-to-scalar ratio [Formula: see text] within the frame of the Starobinsky inflationary model using the improved uniform approximation method and the third-order phase-integral method. We compare our results with those obtained with numerical integration and the slow-roll approximation to second-order. We have obtained consistent values of [Formula: see text] using the different approximations, and [Formula: see text] is inside the interval reported by observations.


Author(s):  
Jabar Hassan ◽  
David E. Grow

We introduce new reproducing kernel Hilbert spaces on a trapezoidal semi-infinite domain $B_{\infty}$ in the plane. We establish uniform approximation results in terms of the number of nodes on compact subsets of $B_{\infty}$ for solutions to nonhomogeneous hyperbolic partial differential equations in one of these spaces, $\widetilde{W}(B_{\infty})$. Furthermore, we demonstrate the stability of such solutions with respect to the driver. Finally, we give an example to illustrate the efficiency and accuracy of our results.


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Mohd Qasim ◽  
Asif Khan ◽  
Zaheer Abbas ◽  
Qing-Bo Cai

AbstractThe aim of this paper is to study a new generalization of Lupaş-type operators whose construction depends on a real-valued function ρ by using two sequences $u_{m} $ u m and $v_{m}$ v m of functions. We prove that the new operators provide better weighted uniform approximation over $[0,\infty )$ [ 0 , ∞ ) . In terms of weighted moduli of smoothness, we obtain degrees of approximation associated with the function ρ. Also, we prove Voronovskaya-type theorem, quantitative estimates for the local approximation.


2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Ting Chen ◽  
Fusheng Lv ◽  
Wenchang Sun

<p style='text-indent:20px;'>In this paper, we introduce frames with the uniform approximation property (UAP). We show that with a UAP frame, it is efficient to recover a signal from its frame coefficients with one erasure while the recovery error is smaller than that with the ordinary recovery algorithm. In fact, our approach gives a balance between the recovery accuracy and the computational complexity.</p>


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