Results 51 to 60 of about 156 (155)

Reachability of a second-order integro-differential equation on Riemannian manifold for a viscoelasticity model

Electronic Journal of Differential Equations, 2019
We study a reachability problem for a second-order integro-differential equation on a finite-dimensional Riemannian manifold, which is a model equation for viscoelasiticity.
Kang Zhou
doaj  

An Inverse Source Problem for Singular Parabolic Equations with Interior Degeneracy

Abstract and Applied Analysis, 2018
The main purpose of this work is to study an inverse source problem for degenerate/singular parabolic equations with degeneracy and singularity occurring in the interior of the spatial domain.
Khalid Atifi, Idriss Boutaayamou, Hamed Ould Sidi, Jawad Salhi   +3 more
doaj   +1 more source

On the boundary of an immediate attracting basin of a hyperbolic entire function

Journal of the London Mathematical Society, Volume 111, Issue 3, March 2025.
Abstract Let f$f$ be a transcendental entire function of finite order which has an attracting periodic point z0$z_0$ of period at least 2. Suppose that the set of singularities of the inverse of f$f$ is finite and contained in the component U$U$ of the Fatou set that contains z0$z_0$. Under an additional hypothesis, we show that the intersection of ∂U$\
Walter Bergweiler, Jie Ding
wiley   +1 more source

Inverse Source Problem for a Singular Parabolic Equation with Variable Coefficients

Mathematics
We consider a parabolic equation with a singular potential in a bounded domain Ω⊂Rn. The main result is a Lipschitz stability estimate for an inverse source problem of determining a spatial varying factor f(x) of the source term R(x,t)f(x).
Xue Qin, Shumin Li
doaj   +1 more source

Global Lipschitz stability for an inverse coefficient problem for a mean field game system

Mathematical Methods in the Applied Sciences, Volume 48, Issue 3, Page 3858-3870, February 2025.
For an inverse coefficient problem of determining a state‐varying factor in the corresponding Hamiltonian for a mean field game system, we prove the global Lipschitz stability by spatial data of one component and interior data in an arbitrarily chosen subdomain over a time interval. The proof is based on Carleman estimates with different norms.
Oleg Imanuvilov, Masahiro Yamamoto
wiley   +1 more source

The symplectic density property for Calogero–Moser spaces

Journal of the London Mathematical Society, Volume 111, Issue 2, February 2025.
Abstract We introduce the symplectic density property and the Hamiltonian density property together with the corresponding versions of Andersén–Lempert theory. We establish these properties for the Calogero–Moser space Cn$\mathcal {C}_n$ of n$n$ particles and describe its group of holomorphic symplectic automorphisms.
Rafael B. Andrist, Gaofeng Huang
wiley   +1 more source

Null controllability of a model in population dynamics

Electronic Journal of Differential Equations, 2014
In this article, we study the null controllability of a linear model with degenerate diffusion in population dynamics. We develop first a Carleman type inequality for the adjoint system of an intermediate model, and then an observability inequality.
Younes Echarroudi, Lahcen Maniar
doaj  

Carleman Type Estimates in an Anisotropic Case and Applications

Journal of Differential Equations, 1993
We give proofs and some further applications of estimates announced in the author's note [Sov. Math. Dokl. 22, 639-642 (1980); transl. from Dokl. Akad. Nauk SSSR 255, 18-21 (1980; Zbl 0468.35030)]. These results extend those of \textit{L. Hörmander} [Linear partial differential operators, Springer, Berlin etc.
openaire   +2 more sources

On an Empirical Likelihood Based Solution to the Approximate Bayesian Computation Problem

Statistical Analysis and Data Mining: The ASA Data Science Journal, Volume 17, Issue 5, October 2024.
ABSTRACT Approximate Bayesian computation (ABC) methods are applicable to statistical models specified by generative processes with analytically intractable likelihoods. These methods try to approximate the posterior density of a model parameter by comparing the observed data with additional process‐generated simulated data sets.
Sanjay Chaudhuri, Subhroshekhar Ghosh, Kim Cuc Pham   +2 more
wiley   +1 more source