Results 91 to 100 of about 26,442 (220)
Some perturbation results of Kirchhoff type equations via Morse theory
Fixed Point Theory and Applications, 2020 In this paper, we consider the following Kirchhoff type equation: { − ( a + b ∫ Ω | ∇ u | 2 d x ) Δ u = f ( x , u ) in Ω , u = 0 on ∂ Ω , $$ \textstyle\begin{cases} - (a+b \int _{\varOmega } \vert \nabla u \vert ^{2}\,dx ) \Delta u= f(x,u) &\text{in } \
Mingzheng Sun, Yutong Chen, Rushun Tian
doaj +1 more source
Kirchhoff equations in generalized Gevrey spaces: local existence, global existence, uniqueness [PDF]
, 2009 In this note we present some recent results for Kirchhoff equations in generalized Gevrey spaces. We show that these spaces are the natural framework where classical results can be unified and extended.
Ghisi, Marina, Gobbino, Massimo
core +2 more sources
Multiple critical points for a class of nonlinear functionals
, 2010 In this paper we prove a multiplicity result concerning the critical points of a class of functionals involving local and nonlocal nonlinearities. We apply our result to the nonlinear Schrodinger-Maxwell system and to the nonlinear elliptic Kirchhoff ...
Azzollini, Antonio +2 more
core +1 more source
Hardware‐Based On‐Chip Learning Using a Ferroelectric AND‐Type Array With Random Synaptic Weights
Advanced Intelligent Systems, EarlyView.This work demonstrates an energy‐efficient on‐chip learning system using an Metal‐Ferroelectric‐Insulator‐Semiconductor FeAND synaptic array. By employing a feedback alignment scheme with a separate backward array using fixed random weights, the system overcomes directional limitations of AND‐type arrays and achieves robust, low‐power learning suitable
Minsuk Song +8 more
wiley +1 more source
Liouville-type theorem for Kirchhoff equations involving Grushin operators
Boundary Value Problems, 2020 The aim of this paper is to prove the Liouville-type theorem of the following weighted Kirchhoff equations: 0.1 − M ( ∫ R N ω ( z ) | ∇ G u | 2 d z ) div G ( ω ( z ) ∇ G u ) = f ( z ) e u , z = ( x , y ) ∈ R N = R N 1 × R N 2 $$\begin{aligned} \begin ...
Yunfeng Wei, Caisheng Chen, Hongwei Yang
doaj +1 more source
Device‐Level Implementation of Reservoir Computing With Memristors
Advanced Intelligent Systems, EarlyView.Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley +1 more source
Strong Solutions and Global Attractors for Kirchhoff Type Equation
Mathematical Problems in Engineering, 2018 We study the long-time behavior of the Kirchhoff type equation with linear damping. We prove the existence of strong solution and the semigroup associated with the solution possesses a global attractor in the higher phase space.
openaire +2 more sources
A Novel Milli‐Scale Magnetic Robot Exploiting Rotation for Controlled Magnetic Particles Release
Advanced Intelligent Systems, EarlyView.Delivering magnetic particles can become a game changer in minimally invasive medicine. To cope with this challenge, a magnetically actuated milli‐scale carrier leveraging rotation to perform on‐demand tunable release of magnetic particles across multiple release events is presented.
Giordano De Angelis +3 more
wiley +1 more source
Mathematical Modelling and AnalysisIn this paper, our focus lies in addressing the Dirichlet problem associated with a specific class of critical anisotropic elliptic equations of Schrödinger-Kirchhoff type.
Nabil Chems Eddine +2 more
doaj +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
Advanced Intelligent Systems, EarlyView.This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source