Results 101 to 110 of about 4,815,078 (315)
Advanced Materials, EarlyView.ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
Uniform Exponential Stability of Discrete Evolution Families on Space of p-Periodic Sequences
Abstract and Applied Analysis, 2014 We prove that the discrete system ζn+1=Anζn is uniformly exponentially stable if and only if the unique solution of the Cauchy problem ζn+1=Anζn+eiθn+1zn+1, n∈Z+, ζ0=0, is bounded for any real number θ and any p-periodic sequence z(n) with z(0)=0. Here,
Yongfang Wang +4 more
doaj +1 more source
Advanced Materials, EarlyView.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
Electronic Journal of Differential Equations, 2002 We prove that the evolution semigroup on $AAP_0(mathbb{R}_+, X)$ is strongly continuous. Then we prove some properties of the generator of this evolution semigroup and show some applications in the theory of inequalities.
Constantin Buse
doaj
A Generalization for Theorems of Datko and Barbashin Type
Journal of Function Spaces, 2015 The goal of the paper is to give some characterizations for the uniform exponential stability of evolution families by unifying the discrete-time versions of the Barbashin-type theorem and the Datko-type theorem.
Pham Viet Hai
doaj +1 more source
Posterior concentration rates for infinite dimensional exponential families
, 2012 In this paper we derive adaptive non-parametric rates of concentration of the posterior distributions for the density model on the class of Sobolev and Besov spaces.
V. Rivoirard, J. Rousseau
semanticscholar +1 more source
Likelihood Ratio Exponential Families
CoRR, 2020 The exponential family is well known in machine learning and statistical physics as the maximum entropy distribution subject to a set of observed constraints, while the geometric mixture path is common in MCMC methods such as annealed importance sampling.
Rob Brekelmans +4 more
openaire +2 more sources
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks [PDF]
We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs ...
David R. Hunter +4 more
core +1 more source
Admissibility and Non-Uniform Dichotomy for Differential Systems [PDF]
, 2004 The problem of nonuniform exponential dichotomy of linear differential systems in Banach spaces is discussed. It is established a connection between the admissibility of a pair of certain function spaces which are translations invariant, on one hand ...
Preda, Ciprian I, Dragomir, Sever S
core