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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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Online Regulation of Unstable LTI Systems from a Single Trajectory

TL;DR: The notion of ''regularizability'' for linear systems that gauges the capacity of a system to be regulated in finite-time in contrast to its asymptotic behavior is introduced and the Data-GuidedRegulation (DGR) synthesis is proposed that regulates the underlying states while also generating informative data that can be used for data-driven stabilization or system identification.
Journal ArticleDOI

Forecasting the industrial production using alternative factor models and business survey data

TL;DR: This paper compares the forecasting performance of three alternative factor models based on business survey data for the industrial production in Italy and shows that the three factor models have a better performance than that of a simple autoregressive benchmark model regardless of the specification and estimation methods.
Journal ArticleDOI

Dynamic behavior of shallow founded historic towers: validation of simplified approaches for seismic analyses

TL;DR: In this paper, the authors present a simple but consistent framework for this kind of analysis using experimental data from a monitoring system installed on the Ghirlandina tower, which can provide reliable estimates of the input motion and of the dynamic stiffness of the soil-foundation system.
Dissertation

Data mining and machine learning for environmental systems modelling and analysis

TL;DR: This work focuses on adapting and developing a new Nonlinear AutoRegressive with eXogenous inputs (NARX) framework, and its application to analyse some environmental case studies, and introduces a package in the R programming language for the construction of NARX models.
Journal ArticleDOI

Saccade Adaptation and Visual Uncertainty.

TL;DR: It is suggested that the saccadic system uses different position signals for adapting dysmetric saccades and for generating a trans-saccadic stable visual percept, explaining that saccade adaptation is found to be independent of visual uncertainty.
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.