Results 71 to 80 of about 11,917 (304)

Estimation of Star-Shaped Distributions

Risks, 2016
Scatter plots of multivariate data sets motivate modeling of star-shaped distributions beyond elliptically contoured ones. We study properties of estimators for the density generator function, the star-generalized radius distribution and the density in a
Eckhard Liebscher, Wolf-Dieter Richter
doaj   +1 more source

Dynamic Analysis of Stochastic Reaction-Diffusion Cohen-Grossberg Neural Networks with Delays

Advances in Difference Equations, 2009
Stochastic effects on convergence dynamics of reaction-diffusion Cohen-Grossberg neural networks (CGNNs) with delays are studied. By utilizing Poincaré inequality, constructing suitable Lyapunov functionals, and employing the method of stochastic ...
Pan Jie, Zhong Shouming
doaj   +2 more sources

Almost Sure Convergence for the Robbins-Monro Process

The Annals of Probability, 1976
In this paper we investigate the almost sure convergence of the Robbins-Monro process $x_{n+1} = x_n - a_n(y_n - \alpha)$ under assumptions about the conditional distribution of $y_n$ given $x_n$ which involve the existence of first moments or something closely related. The process $x_n$ can converge almost surely even when the series $\sum^\infty_{n=1}
Goodsell, C. A., Hanson, D. L.
openaire   +3 more sources

Triple Junctions as Dislocation‐Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation

Advanced Engineering Materials, EarlyView.
Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink, Saba Saood, Peter Schweizer, Jörg Neugebauer, Gerhard Dehm   +4 more
wiley   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

On Quasi-Monotone Stochastic Variational Inequalities with Applications

Axioms
This paper studies an efficient method for solving stochastic optimization problems formulated as stochastic variational inequalities with a quasi-monotone operator, where the cost function extends the classical monotone and pseudomonotone operators. Our
Mohammad Dilshad, Ibrahim Al-Dayel, Francis O. Nwawuru, Jeremiah N. Ezeora   +3 more
doaj   +1 more source

Molecular Adsorbing Host•Guest (MAHG) Crystals: A New Paradigm for Porous Materials?

Advanced Functional Materials, EarlyView.
Networking! Introduction of guest molecules in macrocycles before crystallization profoundly influences the material obtained in terms of structure and function. Beside simplicity and porous space improvement, this approach is endowed with a huge potential given the myriad of potential guest molecules that can be used to tune this burgeoning class of ...
Ingrid Suzana, Michel Giorgi, Anthony Kermagoret, Alexandre Martinez, David Bardelang   +4 more
wiley   +1 more source

Applications of Complex Uncertain Sequences via Lacunary Almost Statistical Convergence

Axioms
We explore the realm of uncertainty theory by investigating diverse notions of convergence and statistical convergence concerning complex uncertain sequences.
Xiu-Liang Qiu, Kuldip Raj, Sanjeev Verma, Samrati Gorka, Shixiao Xiao, Qing-Bo Cai   +5 more
doaj   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Convergence rate of principal component analysis with local-linear smoother for functional data under a unified weighing scheme

Statistical Theory and Related Fields, 2020
The unified weighing scheme for the local-linear smoother in analysing functional data can deal with data that are dense, sparse or of neither type. In this paper, we focus on the convergence rate of functional principal component analysis using this ...
Xingyu Yan, Xiaolong Pu, Yingchun Zhou, Xiaolei Xun   +3 more
doaj   +1 more source