Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Naveed Gul"'
Publikováno v:
Econometrics, Vol 12, Iss 2, p 12 (2024)
Air pollution, especially ground-level ozone, poses severe threats to human health and ecosystems. Accurate forecasting of ozone concentrations is essential for reducing its adverse effects. This study aims to use the functional time series approach
Externí odkaz:
https://doaj.org/article/b4f622a76a6e480b982283f475f29f69
This paper investigates the central role played by the Hamiltonian in continuous-time nonlinear optimal control problems. We show that the strict convexity of the Hamiltonian in the control variable is a sufficient condition for the existence of a un
Externí odkaz:
http://arxiv.org/abs/2404.08621
This paper considers the infinite horizon optimal control problem for nonlinear systems. Under the condition of nonlinear controllability of the system to any terminal set containing the origin and forward invariance of the terminal set, we establish
Externí odkaz:
http://arxiv.org/abs/2403.16979
Autor:
Narayanan, Sriram, Mohamed, Mohamed Naveed Gul, Nayak, Indranil, Chakravorty, Suman, Kumar, Mrinal
This paper discusses the predictive capability of Dynamic Mode Decomposition (DMD) in the context of orbital mechanics. The focus is specifically on the Hankel variant of DMD which uses a stacked set of time-delayed observations for system identifica
Externí odkaz:
http://arxiv.org/abs/2401.13784
In this paper, we consider the infinite horizon optimal control problem for nonlinear systems. Under the conditions of controllability of the linearized system around the origin, and nonlinear controllability of the system to a terminal set containin
Externí odkaz:
http://arxiv.org/abs/2304.00375
This paper considers the problem of system identification for linear time varying systems. We propose a new system realization approach that uses an "information-state" as the state vector, where the "information-state" is composed of a finite number
Externí odkaz:
http://arxiv.org/abs/2211.10583
This paper develops a data-based approach to the closed-loop output feedback control of nonlinear dynamical systems with a partial nonlinear observation model. We propose an information state based approach to rigorously transform the partially obser
Externí odkaz:
http://arxiv.org/abs/2107.08086
We consider the problem of Reinforcement Learning for nonlinear stochastic dynamical systems. We show that in the RL setting, there is an inherent ``Curse of Variance" in addition to Bellman's infamous ``Curse of Dimensionality", in particular, we sh
Externí odkaz:
http://arxiv.org/abs/2011.10829
We consider the problem of nonlinear stochastic optimal control. This problem is thought to be fundamentally intractable owing to Bellman's "curse of dimensionality". We present a result that shows that repeatedly solving an open-loop deterministic p
Externí odkaz:
http://arxiv.org/abs/2004.01041
We consider the problem of robotic planning under uncertainty. This problem may be posed as a stochastic optimal control problem, complete solution to which is fundamentally intractable owing to the infamous curse of dimensionality. We report the res
Externí odkaz:
http://arxiv.org/abs/2002.10505