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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

Adaptive Kalman filtering for multi-step ahead traffic flow prediction

TL;DR: This study proposes solving a multi-step ahead prediction problem as a filtering one by considering pseudo-observations coming from the averaged historical flow or the output of other predictors in the literature, based on adaptive Kalman filtering theory.
Journal ArticleDOI

Effect of age on complexity and causality of the cardiovascular control: comparison between model-based and model-free approaches.

TL;DR: The framework was applied to study age-related modifications of complexity and causality in healthy humans in supine resting and during standing and found that MF approaches are more efficient than the MB method when nonlinear components are present and the reverse situation holds in presence of high dimensional embedding spaces.
Journal ArticleDOI

Identifiability of linear dynamic networks

TL;DR: The notion of network identifiability is introduced, as a property of a parametrized model set, that ensures that different network models can be distinguished from each other when performing identification on the basis of measured data.
Journal ArticleDOI

On Cyclostationarity Based Spectrum Sensing Under Uncertain Gaussian Noise

TL;DR: The formulation allows us to simplify the spectrum sensing detector and obviates the need for estimating an unwieldy covariance matrix needed in some prior works and are computationally cheaper than the Dandawate-Giannakis and related approaches while having quite similar detection performance for a given false alarm rate.
Journal ArticleDOI

Toward Smart Embedded Systems: A Self-aware System-on-Chip (SoC) Perspective

TL;DR: A System-on-Chip perspective is used to show how the CyberPhysical System- on-Chip (CPSoC) exemplar platform achieves self-awareness through a combination of cross-layer sensing, actuation, self-aware adaptations, and online learning.
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.