Titlebook: Approximation and Computation in Science and Engineering; Nicholas J. Daras,Themistocles M. Rassias Book 2022 Springer Nature Switzerland

同音

Ergebnisse der Chirurgie und OrthopädieLet . be a convex function on .. The associated two variables . . is defined by . In this paper, we establish some basic and double integral inequalities for the perspective function . defined above. Some double integral inequalities in the case of rectangles, squares, and circular sectors are also given.

旧石器时代

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arbiter

Rearrangements, ,-Superadditivity and Jensen-Type Inequalities,We deal here with the minimum and the maximum of . and of . obtained by using rearrangement techniques. The results depend on the arrangement of . and are used in proving Jensen-type inequalities.

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The Asymptotic Expansion for a Class of Convergent Sequences Defined by Integrals,We obtain the complete asymptotic expansion of the sequence defined by ., where the functions . and . satisfy various conditions. The main result is applied in Sect. 4 to find the complete asymptotic expansion of some classical sequences.

惊呼

Finite Shift-Invariant Subspaces of Periodic Functions: Characterization, Approximation, and ApplicWe discuss approximations of square integrable periodic functions by their projections in finite shift-invariant subspaces and highlight the role of principal shift invariance. We also show how we may produce a variety of sampling representations based on finite frame theory and we discuss some applications.

钩针织物

GNAW

CT-angiography

Hermite-Hadamard-Type Integral Inequalities for Perspective Function,Let . be a convex function on .. The associated two variables . . is defined by . In this paper, we establish some basic and double integral inequalities for the perspective function . defined above. Some double integral inequalities in the case of rectangles, squares, and circular sectors are also given.

易弯曲

On the Maximum Value of a Multi-variable Function,In this paper, we find the maximum value of a multi-variable function, related by an optimization problem. Our method of maximizing this function is geometric, without applying the partial derivatives tests and the concept of Hessian matrix.