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System Identification I

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The article was published on 2012-12-11. It has received 1704 citations till now. The article focuses on the topics: Nonlinear system identification & System identification.

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Proceedings ArticleDOI

Optimally weighted music algorithm for frequency estimation of real harmonic sinusoids

TL;DR: An optimally weighted harmonic multiple signal classification (OW-HMUSIC) estimator is devised by making use of the subspace technique and Markov-based eigenanalysis to address the problem of fundamental frequency estimation for real harmonic sinusoids.
Journal ArticleDOI

Machine learning‐based automatic operational modal analysis: A structural health monitoring application to masonry arch bridges

TL;DR: A novel multi‐stage clustering algorithm for automatic OMA (AOMA) is tested and validated for SHM applications—specifically, for damage detection and severity assessment—to a masonry arch bridge.
Journal ArticleDOI

Output-only identification of input–output models

TL;DR: This paper introduces transmissibility-based system identification (TBSID), which uses estimates of two transmissibilities to identify the complete dynamics from two unmeasured inputs to two measured outputs.
Journal ArticleDOI

Bayesian identification of electromechanical properties in piezoelectric energy harvesters

TL;DR: The model updating of the electro-mechanical properties of Piezoelectric Energy Harvesters using experimental data within a Bayesian inference setting is discussed, offering an elegant approach to calibrate PEH numerical/analytical model or identify variability trends for the PEH manufacturing process.
Journal ArticleDOI

Explaining COVID-19 outbreaks with reactive SEIRD models.

TL;DR: This work seeks to explain the diversity in epidemic progressions by considering an extension to the compartmental SEIRD model, which uses a neural network to predict the infection rate as a function of time and of the prevalence of the disease.
References
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Book

System Identification: Theory for the User

Lennart Ljung
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Journal ArticleDOI

Deep learning in neural networks

TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Journal ArticleDOI

Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control

TL;DR: This work extends the Koopman operator to controlled dynamical systems and applies the Extended Dynamic Mode Decomposition (EDMD) to compute a finite-dimensional approximation of the operator in such a way that this approximation has the form of a linearcontrolled dynamical system.
Journal ArticleDOI

A Tour of Reinforcement Learning: The View from Continuous Control

TL;DR: The authors surveys reinforcement learning from the perspective of optimization and control, with a focus on continuous control applications, and reviews the general formulation, terminology, and techniques for reinforcement learning for continuous control.
Journal ArticleDOI

SPICE: A Sparse Covariance-Based Estimation Method for Array Processing

TL;DR: This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing, obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many- snapshot cases but can be used even in single-snapshot situations.