Results 71 to 80 of about 57,660 (268)
Option pricing mechanisms driven by backward stochastic differential equations
This study investigates an option pricing method called g-pricing based on backward stochastic differential equations combined with deep learning.
Yufeng Shi, Bin Teng, Sicong Wang
doaj +1 more source
Numberical Method for Backward Stochastic Differential Equations
Let \(W\) be a \(d\)-dimensional Brownian motion. The authors develop a new method of approximating solutions \(Y\) of the multidimensional backward stochastic differential equation (BSDE) \[ dY_t= -f(t, Y_t)dt+ Z_t dW_t,\quad t\in [0,T], \] with a continuous driver \(f\) which is Lipschtz in the \(y\)-variable and independent of \(z\).
Ma, Jin +3 more
openaire +2 more sources
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho +3 more
wiley +1 more source
In the realm of dynamical systems described by deterministic differential equations used in biomathematical modeling, two types of random events influence the populations involved in the model: the first one is called environmental noise, due to factors ...
Roberto Macrelli +2 more
doaj +1 more source
Monotonic Limit Properties for Solutions of BSDEs with Continuous Coefficients
This paper investigates the monotonic limit properties for the minimal and maximal solutions of certain one-dimensional backward stochastic differential equations with continuous coefficients.
ShengJun Fan, Xing Song, Ming Ma
doaj +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
In this paper, a solution is given to reflected backward doubly stochastic differential equations when the barrier is not necessarily right-continuous, and the noise is driven by two independent Brownian motions and an independent Poisson random measure.
Mohamed Marzougue, Yaya Sagna
doaj +1 more source
An Aloe‐pinspired droplet electricity generator (A‐DEG) overcomes the limited energy collection zone of conventional DEGs by guiding impact droplets through a channeling midrib and artificial cuticle. The channeling midrib induces uni‐directional droplet spreading, while the artificial cuticle on the midrib further reinforces this behavior through its ...
Gibeom Lee +8 more
wiley +1 more source
Reflected BSDEs with default time and irregular obstacles
In this note, we study reflected backward stochastic differential equations with a default time, where the reflecting obstacle is not necessarily right-continuous.
Elmansouri, Badr
doaj +1 more source
A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations
This paper extends the idea of E.Gobet, J.P.Lemor and X.Warin from the setting of Backward Stochastic Differential Equations to that of Backward Doubly Stochastic Differential equations.
Aboura, Omar
core +1 more source

