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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

A Novel Method for the Development of an Idealised Active Roll Stabilisation System Model

TL;DR: A novel approach to a systematic development of functional models for the quantification of the vehicle-control system requirements, verified by applying it to the active roll stabilisation system (ARS).
Proceedings ArticleDOI

Toward Tractable Global Solutions to Maximum-Likelihood Estimation Problems via Sparse Sum-of-Squares Relaxations *

TL;DR: A computationally tractable method that computes the maximum-likelihood parameter estimates with posterior certification of global optimality via the concept of sum-of-squares polynomials and sparse semidefinite relaxations is proposed.
Journal ArticleDOI

Sparse vector autoregressive modeling of audio signals and its application to the elimination of impulsive disturbances

TL;DR: A new method for elimination of impulsive disturbances from stereo audio signals is presented, based on a sparse vector autoregressive signal model, made up of two components: one taking care of short-term signal correlations, and the other onetaking care of long-term correlations.
Journal ArticleDOI

Application of Optimal Control Algorithm to Inertia Friction Welding Process

TL;DR: The objective of this brief is to develop optimal control algorithms which use feedback from the upset and angular orientation and are able to reach the necessary accuracy.
Journal ArticleDOI

Estimation of impulse response functions in two-output systems

TL;DR: In this paper, a single input-double output (SIDO) linear time-invariant (LTI) system is considered, whose impulse response function (IRF) is assumed to have one unknown component.
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.