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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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Design of an Adaptive Controller with Online Identification Applied to a Pressure Tank

TL;DR: In this article, an adaptive controller for controlling autotuning pressure was developed for a pressure tank using online identification to obtain the mathematical model of the system, which reached a convergence time of 1 s, an identification with extended least squares, a settling time of 10 s and steady-state error of 3% for the controlled variable.

Visually induced and spontaneous behavior in the zebrafish larva

Adrien Jouary
TL;DR: In the absence of salient sensory cues, zebrafish larva spontaneously produces stereotypical tail movements, similar to those produced during goal-driven navigation, suggesting that larva rely on real-time visual feedback during swimming.
Proceedings ArticleDOI

Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation

TL;DR: Estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in time and backward in time, respectively.
Journal ArticleDOI

Application of singular spectrum analysis to identify the degrading structure using deteriorating distributed element model

TL;DR: In this article, a new system identification technique is applied by using the deteriorating distributed element (DDE) model to simulate the hysteretic behavior of a degrading structure, and the evolutionary properties of the progressive stiffness degradation behavior of reinforced concrete structure can be observed from the identified model parameters.
Proceedings ArticleDOI

Generalized binary noise stimulation enables time-efficient identification of input-output brain network dynamics

TL;DR: A generalized binary noise modulated stimulation pattern is designed that achieves time-efficient identification of IO dynamics by utilizing the time-constant information of the network.
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.