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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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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.
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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.
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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.
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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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Effects of liquefiable soil and bridge modelling parameters on the seismic reliability of critical structural components

TL;DR: In this paper, the authors investigated the sensitivity of seismic fragility estimates for bridge components to variation in structural and liquefiable soil modelling parameters, including undrained shear strength of soil, structural damping ratio, soil shear modulus, gap between deck and abutment, ultimate capacity of soil and fixed and expansion bearing coefficients of friction.
Journal ArticleDOI

A General Framework for Predictors Based on Bounding Techniques and Local Approximation

TL;DR: A general framework for prediction based on nonparametric local estimation and bounding techniques that covers previous methods proposed in the literature is presented and new predictors based on this framework are proposed.
Journal ArticleDOI

Nonlinear-Adaptive Mathematical System Identification

Timothy Sands
- 30 Nov 2017 - 
TL;DR: This article describes using the controller to serve as a novel computational approach for mathematical system identification by reversing paradigms that normally utilize mathematical models as the basis for nonlinear adaptive controllers.
Journal ArticleDOI

Continuous-time interval model identification of blood glucose dynamics for type 1 diabetes

TL;DR: The results show that the interval model approach allows a much more regular estimation of the parameters and avoids physiologically incompatible parameter estimates.
Journal ArticleDOI

New results on discrete-time delay systems identification

TL;DR: A new approach for simultaneous online identification of unknown time delay and dynamic parameters of discrete-time delay systems is proposed and the gradient algorithm is used to deal with the identification problem.