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Book ChapterDOI

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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Journal ArticleDOI

Nonlinear Dynamic Modelling of Platelet Aggregation via Microfluidic Devices

TL;DR: This paper proposes a simple mathematical model of the main dynamics of platelet aggregation/disaggregation observed experimentally in a novel microfluidic device that approximates a severe arterial stenosis, and suggests that the reduced set of model parameters has the potential to be used as a simplified way to evaluate the biomechanical dynamics of Platelet aggregation.
Proceedings ArticleDOI

Estimating polynomial structures from radar data

TL;DR: This work considers extended objects as extended objects modeled by polynomials along the road, and proposes an algorithm to track each polynomial based on noisy range and bearing detections, typically from a radar.

System identification with input uncertainties : an EM kernel-based approach

TL;DR: Many classical problems in system identification, such as the classical predictionerror method and regularized system Identification, identification of Hammerstein and cascaded systems, blind system ...
Journal ArticleDOI

Model- vs. data-based approaches applied to fault diagnosis in potable water supply networks

TL;DR: Two different fault diagnosis approaches are proposed to deal with the problem of fault diagnosis in potable water supply networks, based on a model-based approach and a data-driven solution meant to exploit the spatial and temporal relationships present in the acquired data streams in order to detect and isolate faults.
Posted Content

Fundamental limitations of network reconstruction

TL;DR: It is found that reconstructing any property of the interaction Matrix is generically as difficult as reconstructing the interaction matrix itself, requiring equally informative temporal data.
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.