Results 91 to 100 of about 8,264 (263)

Kolmogorov\u27s Problem for Completely and Multiply Monotone Functions and the Markov Moment Problem

open access: yes, 2015
In this paper, we present the solution to Kolmogorov’s problem for the classes of multiply monotone and completely monotone functions together with its connections to the Markov moment problem, Hermite-Birkhoff interpolation problem, and other extremal ...
Babenko, Vladyslav   +2 more
core  

Markov′s Theorem Revisited

open access: yes, 1994
The fact that Markov′s Theorem holds for determinate measures is often overlooked and the theorem is stated for measures with compact support as did Markov.
Berg, C., Berg, Christian
core   +1 more source

PPO‐Based Reinforcement Learning for the Semi‐Active Vibration Control of MDOF Platform

open access: yesAI &Innovation, EarlyView.
ABSTRACT Aiming at the coupled vibration problem of a multi‐degree‐of‐freedom (MDOF) vibration isolation platform under eccentric excitation, this paper proposes a semi‐active vibration control strategy based on Proximal Policy Optimization (PPO) ‐based reinforcement learning (PPO RL).
Wei Huang, Jian Xu
wiley   +1 more source

Autonomous Flight Strategy Selection and Interval Maintenance for Aircraft With Unknown Flight Intentions

open access: yesIEEE Access
To enhance the operational safety and efficiency of aircraft under uncertain or unknown flight intentions, a decision-making framework based on Markov Decision Processes with incomplete information (IIG-MDP) is proposed in this paper.
Yang Zhou, Xinmin Tang, Xuanming Ren
doaj   +1 more source

Bounding Option Prices Using SDP With Change Of Numeraire [PDF]

open access: yes
Recently, given the first few moments, tight upper and lower bounds of the no arbitrage prices can be obtained by solving semidefinite programming (SDP) or linear programming (LP) problems.
Berc Rustem, Panos Parpas, Kai Ye
core  

Detecting introgression from phylogenetic invariant site patterns using machine learning

open access: yesApplications in Plant Sciences, EarlyView.
Abstract Premise Detecting historical introgression among populations or species from genomic data is a common goal in evolutionary genetics. Most current methods fall into two major categories: network inference and admixture inference. Network inference (e.g., SNaQ) is computationally challenging and typically requires first reducing large genomic ...
Patrick F. McKenzie, Deren A. R. Eaton
wiley   +1 more source

Quantum Phenomena in Molecular and Biological Systems: A Decoherence‐Based Decision Framework With Falsifiable Predictions and a Failure‐Mode Taxonomy

open access: yesAdvanced Physics Research, EarlyView.
A physics‐grounded framework based on decoherence timescales (τ_dec vs τ_func), Markovian validity, and falsifiability criteria is applied across molecular systems to distinguish where quantum effects are necessary, marginal, or irrelevant. The analysis integrates quantum chemistry, biological quantum mechanisms, and quantum computing under a unified ...
Sarfaraz K. Niazi
wiley   +1 more source

The simple harmonic urn

open access: yes, 2011
We study a generalized Polya urn model with two types of ball. If the drawn ball is red it is replaced together with a black ball, but if the drawn ball is black it is replaced and a red ball is thrown out of the urn.
Crane, E.   +21 more
core   +1 more source

An ontological morphological phylogenetic framework for living and extinct ray‐finned fishes (Actinopterygii)

open access: yesThe Anatomical Record, EarlyView.
Abstract The ray‐finned fishes include one out of every two species of living vertebrates on Earth and have an abundant fossil record stretching 380 million years into the past. The division of systematic knowledge of ray‐finned fishes between paleontologists working on extinct animals and neontologists studying extant species has obscured the ...
Jack Stack
wiley   +1 more source

The Markov moment problem and de Finetti’s theorem: Part I

open access: yes, 2003
The Markov moment problem is to characterize sequences s0,s1,s2,...admitting the representation sn = 1 0 xnf(x)dx, where f(x) is a probability density on [0, 1] and 0 ≤ f(x) ≤ c for almost all x. There are well-known characterizations through complex
David Freedman, Persi Diaconis
core  

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