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
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
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.
Journal ArticleDOI
A new kernel-based approach for linear system identification
TL;DR: A new kernel-based approach for linear system identification of stable systems that model the impulse response as the realization of a Gaussian process whose statistics include information not only on smoothness but also on BIBO-stability.
Journal ArticleDOI
Zebedee: Design of a Spring-Mounted 3-D Range Sensor with Application to Mobile Mapping
TL;DR: The results demonstrate that the six-degree-of-freedom trajectory of a passive spring-mounted range sensor can be accurately estimated from laser range data and industrial-grade inertial measurements in real time and that a quality 3-D point cloud map can be generated concurrently using the same data.
References
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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.
Journal ArticleDOI
Does EMG control lead to distinct motor adaptation
Reva E. Johnson,Reva E. Johnson,Konrad P. Kording,Konrad P. Kording,Levi J. Hargrove,Levi J. Hargrove,Jonathon W. Sensinger,Jonathon W. Sensinger +7 more
TL;DR: A simplified comparison of prosthesis and able-bodied control is created by studying adaptation with three control interfaces: joint angle, joint torque, and EMG to suggest that Bayesian models are useful for describing prosthesis control.
Journal ArticleDOI
Forward and inverse modelling approaches for prediction of light stimulus from electrophysiological response in plants
Shre Kumar Chatterjee,Sanmitra Ghosh,Saptarshi Das,Veronica Manzella,Andrea Vitaletti,Elisa Masi,Luisa Santopolo,Stefano Mancuso,Koushik Maharatna +8 more
TL;DR: In this article, a dynamical model for describing the relationship between light as an environmental stimulus and the electrical response as the measured output for a bay leaf (Laurus nobilis) plant was developed.