Results 61 to 70 of about 373,332 (254)
Asymptotic normality for sums along data-dependent sampling schemes [PDF]
, 2005 Let X_={X_,t^1∈N},..., X_={X_, t^d∈N} be independent sequences of i.i.d. real-valued random variables and let S_t=S_+…+S_ where t=(t^1,...,t^d) and S_=Σ_≤t^i-μ_i)/σ_i), i=1,...,d.
Shikimi, Takuhisa
core
Advanced Robotics Research, EarlyView.This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka +3 more
wiley +1 more source
On Asymptotic Normality in Stochastic Approximation
The Annals of Mathematical Statistics, 1968 A new method, simpler than previous methods due to Chung (1954) and Sacks (1958), is used to prove Theorem 2.2 below, which implies in a simple way all known results on asymptotic normality in various cases of stochastic approximation. Two examples of application are concerned with Venter's (1967) extension of the RM method and Fabian's (1967 ...
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Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling
Advanced Robotics Research, EarlyView.This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou +4 more
wiley +1 more source
Asymptotic normality in the problem of selfish parking [PDF]
Vestnik of Saint Petersburg University. Mathematics. Mechanics. Astronomy, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ananjevskii, S. M., Kryukov, N. A.
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Advanced Science, EarlyView.Computational simulations of tumor evolution are increasingly used to infer the rules underlying cancer growth, with the goal of one day recommending tailored treatments. Here we show that the properties of lung cancer sequencing data are best replicated by a model which assumes that cells compete both to proliferate and survive. ABSTRACT Computational
Helena Coggan +5 more
wiley +1 more source
Mathematics, 2020 In this paper, the reliability of a k-component system, in which all components are subject to common stress, is considered. The multicomponent system will continue to survive if at least s out of k components’ strength exceed the common stress.
Lauren Sauer, Yuhlong Lio, Tzong-Ru Tsai
doaj +1 more source
Asymptotic Normality in Nonparametric Methods
The Annals of Mathematical Statistics, 1968 Let $U_1, U_2, \cdots, U_N$ be a random sample from a population with a continuous distribution function and $R_i, i = 1, \cdots, N,$ be the rank of $U_i$ among the $N$ observations. Asymptotic normality is studied for the statistics of the type \begin{equation*}\tag{0.1} \sum^N_{i=1} \sum^N_{j=1} c_{ij}a_N(R_i/N, R_j/N),\end{equation*} where constants
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Asymptotic Normality of Some Graph Sequences [PDF]
Graphs and Combinatorics, 2015 For a simple finite graph G denote by {G \brace k} the number of ways of partitioning the vertex set of G into k non-empty independent sets (that is, into classes that span no edges of G). If E_n is the graph on n vertices with no edges then {E_n \brace k} coincides with {n \brace k}, the ordinary Stirling number of the second kind, and so we refer to {
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Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
Advanced Science, EarlyView.StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source