Results 21 to 30 of about 2,900 (252)

A Convolution Approach on Partial Sums of Certain Harmonic Univalent Functions

International Journal of Mathematics and Mathematical Sciences, 2012
The purpose of the present paper is to establish some new results giving the sharp bounds of the real parts of ratios of harmonic univalent functions to their sequences of partial sums by using convolution.
Saurabh Porwal
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Approximation on the sphere by weighted Fourier expansions

Journal of Applied Mathematics, 2005
The main theme of this paper is the approximation on the sphere by weighted sums of spherical harmonics. We give necessary and sufficient conditions on the weights for convergence in both the continuous and the LP cases.
V. A. Menegatto, A. C. Piantella
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Some Upper Bounds for RKHS Approximation by Bessel Functions

Axioms, 2022
A reproducing kernel Hilbert space (RKHS) approximation problem arising from learning theory is investigated. Some K-functionals and moduli of smoothness with respect to RKHSs are defined with Fourier–Bessel series and Fourier–Bessel transforms ...
Mingdang Tian, Baohuai Sheng, Shuhua Wang   +2 more
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A sieve method for shifted convolution sums [PDF]

Duke Mathematical Journal, 2009
To appear in Duke Math. J.
openaire   +4 more sources

A Note on the Tail Behavior of Randomly Weighted Sums with Convolution-Equivalently Distributed Random Variables

Abstract and Applied Analysis, 2013
We investigate the tailed asymptotic behavior of the randomly weighted sums with increments with convolution-equivalent distributions. Our obtained result can be directly applied to a discrete-time insurance risk model with insurance and financial risks ...
Yang Yang, Jun-feng Liu, Yu-lin Zhang
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DATIC: A Data-Aware Time-Domain Computing-in-Memory-Based CNN Processor With Dynamic Channel Skipping and Mapping

IEEE Open Journal of the Solid-State Circuits Society, 2022
Due to the low-power priority of analog delay-based computation, time-domain computing-in-memory (TD-CIM) presents a splendid potential for energy-constrained edge and IoT scenarios deploying convolutional neural networks (CNNs).
Jianxun Yang, Yuyao Kong, Yixuan Li, Chenfu Guo, Hao Sun, Leibo Liu, Shaojun Wei, Jun Yang, Shouyi Yin   +8 more
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New Subclasses of Multivalent Analytic Functions Associated with a Linear Operator

Abstract and Applied Analysis, 2013
Making use of a linear operator, which is defined here by means of the Hadamard product (or convolution), we consider two subclasses and of multivalent analytic functions with negative coefficients in the open unit disk. Some modified Hadamard products,
Ding-Gong Yang, Jin-Lin Liu
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Some Types of Identities Involving the Legendre Polynomials

Mathematics, 2019
In this paper, a new non-linear recursive sequence is firstly introduced. Then, using this sequence, a computational problem involving the convolution of the Legendre polynomial is studied using the basic and combinatorial methods.
Shimeng Shen, Li Chen
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On the Relation Between Fourier Frequency and Period for Discrete Signals, and Series of Discrete Periodic Complex Exponentials

IEEE Open Journal of Signal Processing, 2021
Discrete complex exponentials are almost periodic signals, not always periodic; when periodic, the frequency determines the period, but not viceversa, the period being a chaotic function of the frequency, expressible in terms of Thomae's function.
Alfredo Restrepo, Julian Quiroga, Jairo Hurtado   +2 more
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Differentiation of the Mittag-Leffler Functions with Respect to Parameters in the Laplace Transform Approach

Mathematics, 2020
In this work, properties of one- or two-parameter Mittag-Leffler functions are derived using the Laplace transform approach. It is demonstrated that manipulations with the pair direct–inverse transform makes it far more easy than previous methods to ...
Alexander Apelblat
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