Results 11 to 20 of about 991,733 (290)
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Resilience in Discrete Event Systems
IFAC-PapersOnLine, 2022 This paper explores the notion of resilience of a fault in a DES, as the ability to spontaneously return to a normal behavior, without leaking information about this fault occurrence to an external observer. Resilience expresses some form of insensitivity or robustness, related but different from classical notions like diagnosability or opacity ...
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Entropy, 2022 This paper is concerned with the adaptive event-triggered finite-time pinning synchronization control problem for T-S fuzzy discrete complex networks (TSFDCNs) with time-varying delays.
Xiru Wu +3 more
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On Opacity Verification for Discrete-Event Systems
IFAC-PapersOnLine, 2020 Opacity is an information flow property characterizing whether a system reveals its secret to an intruder. Verification of opacity for discrete-event systems modeled by automata is in general a hard problem. We discuss the question whether there are structural restrictions on the system models for which the opacity verification is tractable.
Jiří Balun +2 more
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A novel simulation method for power electronics: discrete state event driven method
CES Transactions on Electrical Machines and Systems, 2017 In the analysis of power electronics system, it is necessary to simulate ordinary differential equations (ODEs) with discontinuities and stiffness. However, there are many difficulties in using traditional discrete-time algorithms to solve such equations.
Boyang Li +4 more
doaj +1 more source
Vehicular Network Simulation Environment via Discrete Event System Modeling
IEEE Access, 2019 A vehicular ad-hoc network (VANET) enables vehicles to communicate with each other directly or via roadside infrastructure in order to improve road safety and efficiency.
Le Wang +2 more
doaj +1 more source
Towards a DEVS Model Management System for Decision-Making Web Applications
Information, 2023 The discrete event system specification formalism introduced by Zeigler in the 1970s is ideally associated with new technological advances in the web to offer an almost quasi-automatic mechanism for exporting its simulation models associated with ...
Laurent Capocchi +1 more
doaj +1 more source
Supervisory Controller Design for Power System Stability using Hybrid Automata Modeling [PDF]
International Journal of Industrial Electronics, Control and Optimization, 2021 Power systems are categorized as nonlinear dynamical systems, and the importance and complexity associated with their stability have dramatically increased.
Fariba Forouzesh +2 more
doaj +1 more source
Coordination control of discrete-event systems [PDF]
2008 9th International Workshop on Discrete Event Systems, 2008 The concept of a coordinator is proposed for control of modular discrete-event systems. The coordinator makes all subsystems conditionally independent generators as defined in the paper. The coordinator receives part of the partial observations of the subsystems and its task is to satisfy the global part of the specification and of the nonblockingness.
Komenda, J. (Jan), van Schuppen, J. H.
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Discrete event control of nondeterministic systems
Proceedings of 35th IEEE Conference on Decision and Control, 1998 Summary: Nondeterminism in discrete-event systems occurs in many practical situations and often as a result of partial observability of events. For the adequate description of nondeterministic systems and nondeterministic phenomena, the trajectory-model formalism was introduced. This formalism has been used in [\textit{M. Shayman} and \textit{R. Kumar},
Feng Lin, Michael Heymann
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