Results 61 to 70 of about 1,380 (204)

New Variations and Structural Refinements of Discrete Weighted Jensen and Hermite–Hadamard Inequalities Using (α, m)‐Convex Mappings

open access: yesJournal of Mathematics, Volume 2026, Issue 1, 2026.
This article develops new Hermite–Hadamard and Jensen‐type inequalities for the class of (α, m)‐convex functions. New product forms of Hermite–Hadamard inequalities are established, covering multiple distinct scenarios. Several nontrivial examples and remarks illustrate the sharpness of these results and demonstrate how earlier inequalities can be ...
Shama Firdous   +5 more
wiley   +1 more source

Stability for Caputo–Hadamard Fractional Uncertain Differential Equation

open access: yesFractal and Fractional
This paper focuses on the Caputo-Hadamard fractional uncertain differential equations (CH-FUDEs) governed by Liu processes, which combine the Caputo–Hadamard fractional derivative with uncertain differential equations to describe dynamic systems ...
Shida Peng   +4 more
doaj   +1 more source

Green’s Function Approach to Hermite–Hadamard–Mercer Type Fractional Inequalities and Applications

open access: yesJournal of Mathematics, Volume 2026, Issue 1, 2026.
The Hermite–Hadamard–Mercer (HHM) inequality, existing in two well‐established forms, plays a fundamental role in mathematical analysis. This inequality is characterized by three distinct components—namely, the left, middle, and right terms. This study is concerned to obtain novel generalized and refined HHM fractional inequalities by employing for the
Muhammad Zafran   +6 more
wiley   +1 more source

On numerical techniques for solving the fractional logistic differential equation

open access: yesAdvances in Difference Equations, 2019
This paper studied the existence and uniqueness of the solution of the fractional logistic differential equation using Hadamard derivative and integral. Previous work has shown that there is not an exact solution to this fractional model.
Yves Yannick Yameni Noupoue   +2 more
doaj   +1 more source

Hilfer-Prabhakar Derivatives and Some Applications

open access: yes, 2014
We present a generalization of Hilfer derivatives in which Riemann--Liouville integrals are replaced by more general Prabhakar integrals. We analyze and discuss its properties.
Garra, Roberto   +3 more
core   +1 more source

Studies on Fractional Differential Equations With Functional Boundary Condition by Inverse Operators

open access: yesMathematical Methods in the Applied Sciences, Volume 48, Issue 11, Page 11161-11170, 30 July 2025.
ABSTRACT Fractional differential equations (FDEs) generalize classical integer‐order calculus to noninteger orders, enabling the modeling of complex phenomena that classical equations cannot fully capture. Their study has become essential across science, engineering, and mathematics due to their unique ability to describe systems with nonlocal ...
Chenkuan Li
wiley   +1 more source

Blowing‐Up Solution of a System of Fractional Differential Equations With Variable Order

open access: yesMathematical Methods in the Applied Sciences, Volume 48, Issue 9, Page 9726-9743, June 2025.
ABSTRACT We investigated the necessary condition for blowing‐up solutions in finite time of the system u′(t)+(1)D0|tα(t)(u(t)−u0)=|v(t)|q,t>0,q>1,v′(t)+(1)D0|tβ(t)(v(t)−v0)=|u(t)|p,t>0,p>1$$ {u}^{\prime }(t)+{}_{(1)}{D}_{0\mid t}^{\alpha (t)}\left(u(t)-{u}_0\right)={\left|v(t)\right|}^q,\kern0.3em t>0,q>1,{v}^{\prime }(t)+{}_{(1)}{D}_{0\mid t}^{\beta ...
Muhammad Rizki Fadillah, Mokhtar Kirane
wiley   +1 more source

Observer Design for Fractional-Order Polynomial Fuzzy Systems Depending on a Parameter

open access: yesFractal and Fractional
For fractional-order systems, observer design is remarkable for the estimation of unavailable states from measurable outputs. In addition, the nonlinear dynamics and the presence of parameters that can vary over different operating conditions or time ...
Hamdi Gassara   +3 more
doaj   +1 more source

Recovering discrete delayed fractional equations from trajectories

open access: yesMathematical Methods in the Applied Sciences, Volume 48, Issue 7, Page 7630-7640, 15 May 2025.
We show how machine learning methods can unveil the fractional and delayed nature of discrete dynamical systems. In particular, we study the case of the fractional delayed logistic map. We show that given a trajectory, we can detect if it has some delay effect or not and also to characterize the fractional component of the underlying generation model.
J. Alberto Conejero   +2 more
wiley   +1 more source

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