Browsing Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering by Title
Now showing items 1538-1557 of 2897
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Conference Object
Machine learning algorithms for photovoltaic system power output prediction
(2018)Accurate photovoltaic (PV) production forecasting is necessary for the optimal integration of this technology into existing power systems and is important for both grid and plant operators. The purpose of this work is to ...
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Conference Object
Machine Learning for QoT Estimation of Unseen Optical Network States
(2019)We apply deep graph convolutional neural networks for Quality-of-Transmission estimation of unseen network states capturing, apart from other important impairments, the inter-core crosstalk that is prominent in optical ...
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Machine learning-based statistical testing hypothesis for fault detection in photovoltaic systems
(2019)In this paper, we consider a machine learning approach merged with statistical testing hypothesis for enhanced fault detection performance in photovoltaic (PV) systems. The developed method makes use of a machine learning ...
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Conference Object
Marginal analysis on binary pairwise Gibbs random fields
(2011)In this paper, we study marginal problems for a class of binary pairwise Gibbs random fields (BPW-GRFs). Given a BPW-GRF associated with a family of binary positive pairwise potentials, finding the exact marginal for each ...
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Article
Marking observer in labeled petri nets with application to supervisory control
(2017)In this paper, we consider the problem of marking estimation in labeled Petri nets whose initial marking is known to belong to a given convex set, in the presence of silent transitions (i.e., transitions labeled with the ...
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Conference Object
Marking observer of labeled petri nets with uncertainty in the initial marking
(2013)In this paper we consider marking estimation in labeled Petri nets whose initial marking is known to belong to a given convex set. We allow for silent transitions (i.e., transitions labeled with the empty word) and ...
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Conference Object
A mathematical framework for robust control over uncertain communication channels
(2005)In this paper, a mathematical framework for studying robust control over uncertain communication channels is introduced. The theory is developed by 1) Generalizing the classical information theoretic measures to the robust ...
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Mathematical modeling of tumor growth, drug-resistance, toxicity, and optimal therapy design
(2014)
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Max-product algorithms for the generalized multiple-fault diagnosis problem
(2007)In this paper, we study the application of the max-product algorithm (MPA) to the generalized multiple-fault diagnosis (GMFD) problem, which consists of components (to be diagnosed) and alarms/connections that can be ...
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Conference Object
Maximum likelihood diagnosis in partially observable finite state machines
(2005)In this paper we develop a probabilistic approach for fault diagnosis in deterministic finite state machines (FSMs). The proposed approach determines whether the FSM under consideration is faulty or not by observing (part ...
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Maximum likelihood failure diagnosis in finite state machines under unreliable observations
(2010)In this paper, we develop a probabilistic methodology for failure diagnosis in finite state machines based on a sequence of unreliable observations. Given prior knowledge of the input probability distribution but without ...
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Conference Object
Maximum Likelihood parameter estimation from incomplete data via the sensitivity equations: The continuous-time case
(IEEE, 1999)The problem of estimating the parameters for continuous-time partially observed systems is discussed. New exact filters for obtaining Maximum Likelihood (ML) parameter estimates via the Expectation Maximization algorithm ...
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Maximum likelihood parameter estimation from incomplete data via the sensitivity equations: the continuous-time case
(2000)This paper is concerned with maximum likelihood (ML) parameter estimation of continuous-time nonlinear partially observed stochastic systems, via the expectation maximization (EM) algorithm. It is shown that the EM algorithm ...
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Conference Object
Maximum principle for decentralized stochastic differential decision systems
(Institute of Electrical and Electronics Engineers Inc., 2014)In this paper we derive team and Person-by-Person (PbP) optimality conditions for Itô SDEs with nonclassical information structures. The optimality conditions are given in terms of a Hamiltonian System described by coupled ...
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Conference Object