Results 61 to 70 of about 26,127 (206)
Change-point detection for piecewise deterministic Markov processes [PDF]
Automatica, 2018 We consider a change-point detection problem for a simple class of Piecewise Deterministic Markov Processes (PDMPs). A continuous-time PDMP is observed in discrete time and through noise, and the aim is to propose a numerical method to accurately detect both the date of the change of dynamics and the new regime after the change.
Cleynen, Alice, de Saporta, Benoîte
openaire +3 more sources
Maintenance Optimisation of Optronic Equipment
Chemical Engineering Transactions, 2013 As part of optimizing the reliability, Thales Optronics now includes systems that examine the state of its equipment. This function is performed by HUMS (Health & Usage Monitoring System).
C. Baysse +5 more
doaj +1 more source
Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)
Advanced Intelligent Systems, EarlyView.This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley +1 more source
Value passing for communicating piecewise deterministic Markov processes [PDF]
2006 American Control Conference, 2006 In this paper we extend the CPDP model, which is used for compositional specification of PDP-type stochastic hybrid systems, to the value passing CPDP model. With value passing we can express communication of values of continuous variables between CPDP components. We show that the class of value passing CPDPs is closed under composition.
Strubbe, Stefan +2 more
openaire +2 more sources
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Asian Journal of Control, EarlyView.Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
Bisimulation for Communicating Piecewise Deterministic Markov Processes (CPDPs) [PDF]
, 2005 CPDPs (Communicating Piecewise Deterministic Markov Processes) can be used for compositional specification of systems from the class of stochastic hybrid processes formed by PDPs (Piecewise Deterministic Markov Processes). We define CPDPs and the composition of CPDPs, and prove that the class of CPDPs is closed under composition.
Strubbe, S.N., van der Schaft, Arjan
openaire +2 more sources
Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
Communications on Pure and Applied Mathematics, EarlyView.ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
Algorithmic bisimulation for Communicating Piecewise Deterministic Markov Processes [PDF]
Proceedings of the 44th IEEE Conference on Decision and Control, 2006 In this paper we present an algorithm for finding a bisimulation relation for stochastic hybrid systems from the class of CPDPs (Communicating Piecewise Deterministic Markov Processes). We prove that the fixed point of the algorithm forms a bisimulation on the state space of the CPDP.
Strubbe, S.N., van der Schaft, Arjan
openaire +2 more sources
Trait coevolution and causal inference using generalized dynamic phylogenetic models
Methods in Ecology and Evolution, EarlyView.Abstract Phylogenetic comparative methods are widely used to study trait coevolution across biological and cultural domains. The most common methods are phylogenetic generalized linear (mixed) models, phylogenetic path analysis, Pagel's ‘discrete’ method and Ornstein–Uhlenbeck models. While some frameworks like generalized linear mixed models are quite
Erik J. Ringen +3 more
wiley +1 more source
When in Doubt, Tax More Progressively? Uncertainty and Progressive Income Taxation
International Economic Review, EarlyView.ABSTRACT We study the optimal income tax problem under parameter uncertainty about household preferences and wage dynamics. We derive conditions characterizing how such uncertainty affects optimal tax policy. To quantify the effect, we estimate a life‐cycle model using US data and a Bayesian approach.
Minsu Chang, Chunzan Wu
wiley +1 more source