Book ChapterDOI
System Identification I
Biao Huang,Yutong Qi,Akm Monjur Murshed +2 more
- pp 31-56
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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.read more
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Journal ArticleDOI
Parameter estimation approach to banding artifact reduction in balanced steady-state free precession
Marcus Björk,R. Reeve Ingle,Erik Gudmundson,Petre Stoica,Dwight G. Nishimura,Joëlle K. Barral +5 more
TL;DR: The balanced steady‐state free precession pulse sequence has shown to be of great interest due to its high signal‐to‐noise ratio efficiency, but images often suffer from banding artifacts due to off‐resonance effects, which this article aims to minimize.
Book ChapterDOI
Parameter selection methods in inverse problem formulation
TL;DR: Methods for a priori selection of parameters to be estimated in inverse problem formulations (such as Maximum Likelihood, Ordinary and Generalized Least Squares) for dynamical systems with numerous state variables and even larger number of parameters are discussed.
Journal ArticleDOI
Sparse Identification of Nonlinear Functions and Parametric Set Membership Optimality Analysis
TL;DR: A combined l1-relaxed-greedy algorithm is proposed and conditions are given, under which the approximation derived by the algorithm is a sparsest one, and it is shown that the algorithms is able to exactly select the basis functions which define the unknown function and to provide an optimal estimate of their coefficients.
Journal ArticleDOI
Clinical application of a modular ankle robot for stroke rehabilitation
Larry W. Forrester,Anindo Roy,Ronald N. Goodman,Jeremy C. Rietschel,Joseph E. Barton,Hermano Igo Krebs,Hermano Igo Krebs,Richard F. Macko +7 more
TL;DR: A programmatic effort to develop and apply the concept of joint-specific modular robotics to the paretic ankle as a means to improve underlying impairments in distal motor control that may have a significant impact on gait biomechanics and balance.
Journal ArticleDOI
Performance assessment of primary frequency control responses for thermal power generation units using system identification techniques
TL;DR: A new method is proposed to estimate performance metrics for PFC responses via system identification techniques that removes three major limitations of the most widely-used method in contemporary industrial practices.
References
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Book
System Identification: Theory for the User
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
Milan Korda,Igor Mezic +1 more
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
Petre Stoica,Prabhu Babu,Jian Li +2 more
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.