Results 11 to 20 of about 732,831 (345)

Data‐driven performance metrics for neural network learning

International Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri, Mauro Gaggero, Marcello Sanguineti   +2 more
wiley   +1 more source

Architected Lattices with a Topological Transition

Advanced Engineering Materials, EarlyView., 2023
This article develops topological metamaterials showing multidirectional two‐step deformation under compression by embedding contact‐enabled topological mechanisms into lattice structures. Experiments on 3D‐printed 2D and 3D lattices and finite element simulations are conducted to demonstrate the working principle of the topological metamaterials.
Shivam Agarwal, Lihua Jin
wiley   +1 more source

L2-convergence of Yosida approximation for semi-linear backward stochastic differential equation with jumps in infinite dimension [PDF]

Arab Journal of Mathematical Sciences
Purpose – The main motivation of this paper is to present  the Yosida approximation of a semi-linear backward stochastic differential equation in infinite dimension. Under suitable assumption and condition, an L2-convergence rate is established.
Hani Abidi, Rim Amami, Roger Pettersson, Chiraz Trabelsi   +3 more
doaj   +1 more source

Efficient Memristive Stochastic Differential Equation Solver

Advanced Intelligent Systems, 2023
Herein, an efficient numerical solver for stochastic differential equations based on memristors is presented. The solver utilizes the stochastic switching effect in memristive devices to simulate the generation of a Brownian path and employs iterative ...
Xuening Dong, Louis Primeau, Roman Genov, Mostafa Rahimi Azghadi, Amirali Amirsoleimani   +4 more
doaj   +1 more source

STATIONARY SOLUTIONS OF STOCHASTIC DIFFERENTIAL EQUATIONS WITH MEMORY AND STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS [PDF]

Communications in Contemporary Mathematics, 2005
We explore Itô stochastic differential equations where the drift term possibly depends on the infinite past. Assuming the existence of a Lyapunov function, we prove the existence of a stationary solution assuming only minimal continuity of the coefficients.
Jonathan C. Mattingly, Jonathan C. Mattingly, Yuri Bakhtin, Yuri Bakhtin   +3 more
openaire   +2 more sources

Adiabatic elimination in quantum stochastic models [PDF]

, 2007
We consider a physical system with a coupling to bosonic reservoirs via a quantum stochastic differential equation. We study the limit of this model as the coupling strength tends to infinity.
A.C. Doherty, Andrew Silberfarb, C. Cohen-Tannoudji, C.W. Gardiner, C.W. Gardiner, D.F. Walls, E.B. Davies, E.B. Davies, G.C. Papanicolaou, H. Trotter, H.M. Wiseman, I.H. Deutsch, J. Derezinski, J. Gough, J. Gough, J.A. Dunningham, K.S. Wong, L. Accardi, L.-M. Duan, Luc Bouten, R.L. Hudson, T. Kato, T.G. Kurtz, T.G. Kurtz   +23 more
core   +2 more sources

An Averaging Principle for Mckean–Vlasov-Type Caputo Fractional Stochastic Differential Equations

Journal of Mathematics, 2021
In this paper, we want to establish an averaging principle for Mckean–Vlasov-type Caputo fractional stochastic differential equations with Brownian motion.
Weifeng Wang, Lei Yan, Junhao Hu, Zhongkai Guo   +3 more
doaj   +1 more source

Large deviations for stochastic Kuramoto–Sivashinsky equation with multiplicative noise

Nonlinear Analysis, 2021
The Kuramoto–Sivashinsky equation is a nonlinear parabolic partial differential equation, which describes the instability and turbulence of waves in chemical reactions and laminar flames. The aim of this work is to prove the large deviation principle for
Gregory Amali Paul Rose, Murugan Suvinthra, Krishnan Balachandran   +2 more
doaj   +1 more source

A kind of non-zero sum mixed differential game of backward stochastic differential equation

Advances in Difference Equations, 2020
This paper is concerned with a non-zero sum mixed differential game problem described by a backward stochastic differential equation. Here the term “mixed” means that this game problem contains a deterministic control v1 $v_{1}$ of Player 1 and a random ...
Huanjun Zhang
doaj   +1 more source

Probabilistic Representations of Solutions of the Forward Equations [PDF]

, 2007
In this paper we prove a stochastic representation for solutions of the evolution equation $ \partial_t \psi_t = {1/2}L^*\psi_t $ where $ L^* $ is the formal adjoint of an elliptic second order differential operator with smooth coefficients corresponding
Rajeev, B., Thangavelu, S.
core   +2 more sources