Results 101 to 110 of about 7,636,692 (302)
Classical and almost sure local limit theorems
We present and discuss the many results obtained concerning a famous limit theorem, the local limit theorem, which has many interfaces, with Number Theory notably, and for which, in spite of considerable efforts, the question concerning conditions of validity of the local limit theorem, has up to now no satisfactory solution.
Szewczak, Zbigniew S., Weber, Michel
openaire +3 more sources
Block Bootstrap Consistency Under Weak Assumptions [PDF]
This paper weakens the size and moment conditions needed for typical block bootstrap methods (i.e. the moving blocks, circular blocks, and stationary bootstraps) to be valid for the sample mean of Near-Epoch-Dependent functions of mixing processes; they ...
Calhoun, Gray
core
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
We propose a prey predator model with stage structure for prey. A discrete delay and a distributed delay for predator described by an integral with a strong delay kernel are also considered.
Chao Liu, Qingling Zhang
doaj +1 more source
A local convergence theorem for partial sums of stochastic adapted sequences [PDF]
summary:In this paper we establish a new local convergence theorem for partial sums of arbitrary stochastic adapted sequences. As corollaries, we generalize some recently obtained results and prove a limit theorem for the entropy density of an arbitrary ...
Ye, Zhongxing, Yang, Weiguo, Liu, Wen
core +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
The behaviors of semiflexible polymers such as DNA and protein are often reshaped by coupled interactions. Monte Carlo simulations assist in studying these systems. This work recasts the traditional chain‐growth strategy into a new framework: a fixed number of chains grow synchronously, while less relevant chains to the target system are removed and ...
Yihan Zhao, Jizeng Wang
wiley +1 more source
A central limit theorem for realised power and bipower variations of continuous semimartingales [PDF]
Central limit theorem, quadratic variation, bipower variation --Central limit theorem,quadratic variation,bipower ...
Graversen, Svend Erik +3 more
core
A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung +10 more
wiley +1 more source
A bivariate local limit theorem
A random 2-vector in \(X\subset\mathbb{R}^{(2)}\) is said to have a stable distribution if there exist a sequence of i.i.d. vectors \(Y_ n=(Y_ n^{(1)},Y_ n^{(2)})\) and associated 2-vector sequences \(\{b_ n\}\), and \(\{a_ n\}\) with \(b_ n=\{b_ n^{(1)},b_ n^{(2)}\}\), \(a_ n=\{a_ n^{(1)},a_ n^{(2)}\}\), \(a_ n^{(i)}>0\), \(i=1,2\), with \(\{S_ n^{(1)}
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