Results 51 to 60 of about 2,215,169 (319)

CLT for an iterated integral with respect to fBm with H > 1/2

, 2012
We construct an iterated stochastic integral with fractional Brownian motion with H > 1/2. The first integrand is a deterministic function, and each successive integral is with respect to an independent fBm.
Harnett, Daniel, Nualart, David
core   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

Molecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix, Daniel Samaga, Katharina Gehr, Benedek Dankó, Mohamed Schumann, Guido Drexler, Ahmed Alnatsha, Georg Beyer, Ujjwal Mahajan, Martin Selmansberger, Julia Mayerle, Claus Belka, Horst Zitzelsberger, Kirsten Lauber   +13 more
wiley   +1 more source

Existence and Phase Structure of Random Inverse Limit Measures

Mathematics
Analogous to Kolmogorov’s theorem for the existence of stochastic processes describing random functions, we consider theorems for the existence of stochastic processes describing random measures as limits of inverse measure systems. Specifically, given a
B. J. K. Kleijn
doaj   +1 more source

The 𝒮-Transform of Sub-fBm and an Application to a Class of Linear Subfractional BSDEs

Advances in Mathematical Physics, 2013
Let SH be a subfractional Brownian motion with index ...
Zhi Wang, Litan Yan
doaj   +1 more source

Optimal Control Problems of Forward-Backward Stochastic Volterra Integral Equations [PDF]

, 2014
Optimal control problems of forward-backward stochastic Volterra integral equations (FBSVIEs in short) are formulated and studied. A general duality principle is established for linear backward stochastic integral equation and linear stochastic Fredholm ...
Shi, Yufeng, Wang, Tianxiao, Yong, Jiongmin   +2 more
core  

VLSI Implementation of Deep Neural Network Using Integral Stochastic Computing [PDF]

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2015
The hardware implementation of deep neural networks (DNNs) has recently received tremendous attention: many applications in fact require high-speed operations that suit a hardware implementation.
A. Ardakani, François Leduc-Primeau, N. Onizawa, T. Hanyu, W. Gross   +4 more
semanticscholar   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

New stochastic fractional integral and related inequalities of Jensen–Mercer and Hermite–Hadamard–Mercer type for convex stochastic processes

Journal of Inequalities and Applications, 2023
In this investigation, we unfold the Jensen–Mercer ( J − M $\mathtt{J-M}$ ) inequality for convex stochastic processes via a new fractional integral operator.
Fahd Jarad, Soubhagya Kumar Sahoo, Kottakkaran Sooppy Nisar, Savin Treanţă, Homan Emadifar, Thongchai Botmart   +5 more
doaj   +1 more source

Coherent-state path integral versus coarse-grained effective stochastic equation of motion: From reaction diffusion to stochastic sandpiles

, 2016
We derive and study two different formalisms used for non-equilibrium processes: The coherent-state path integral, and an effective, coarse-grained stochastic equation of motion. We first study the coherent-state path integral and the corresponding field
Wiese, Kay Jörg
core   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source