Autoregressive model

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Application of Time Series Methods on Long-Term Structural Monitoring Data for Fatigue Analysis

Eugen Brühwiler, Bartlomiej Wojciech Sawicki, Morteza Ahmadivala

Structural health monitoring (SHM) can be employed to reduce uncertainties in different aspects of structural analysis such as: load modeling, crack development, corrosion rates, etc. Fatigue is one of the main degradation processes of structures that caus ...

2019

Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems With Stochastic Uncertainties

Giancarlo Ferrari Trecate

This paper proposes a novel scalable model-based fault detection and isolation approach for the monitoring of nonlinear large-scale systems, consisting of a network of interconnected subsystems. The fault diagnosis architecture is designed to automatically ...

2019

Measurement of forward top pair production in the dilepton channel in pp collisions at root s=13 TeV

Olivier Schneider, Yiming Li, Guido Haefeli, Christoph Frei, Aurelio Bay, Tatsuya Nakada, Michel De Cian, Luca Pescatore, Frédéric Blanc, François Fleuret

Forward top quark pair production is studied in pp collisions in the mu eb final state using a data sample corresponding to an integrated luminosity of 1.93 fb(-1) collected with the LHCb experiment at a centre-of-mass energy of 13 TeV. The cross-section i ...

Springer Nature2018

Autoregressive moving average graph filters a stable distributed implementation

Andreas Loukas

We present a novel implementation strategy for distributed autoregressive moving average (ARMA) graph filters. Differently from the state of the art implementation, the proposed approach has the following benefits: (i) the designed filter coefficients come ...

Ieee2017

Filtering Random Graph Processes Over Random Time-Varying Graphs

Andreas Loukas

Graph filters play a key role in processing the graph spectra of signals supported on the vertices of a graph. However, despite their widespread use, graph filters have been analyzed only in the deterministic setting, ignoring the impact of stochasticity i ...

Institute of Electrical and Electronics Engineers2017

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