Book ChapterDOI
System Identification I
Biao Huang,Yutong Qi,Akm Monjur Murshed +2 more
- pp 31-56
About:
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
Citations
More filters
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
More filters
Book ChapterDOI
Comments on model validation as set membership identification
TL;DR: By defining the set of models that would pass the chosen model validation test, each is interpreted as a set membership identification method and the important, but perhaps controversial concept of “independence” is focused on to make further selections of models within the thus defined sets.
Journal ArticleDOI
Identification of stochastic nonlinear models using optimal estimating functions
TL;DR: The first part of the paper examines the asymptotic properties of linear prediction error method estimators, which were recently suggested for the identification of nonlinear stochastic dynamical m estimators.
Proceedings ArticleDOI
Comparison of experimental identification methods using measured data from a turbojet engine
TL;DR: This work uses measured data from the small turbojet engine iSTC-21v to create experimental models through programming environment MATLAB/Simulink and gets the amount of the mean absolute error (MAE) and mean absolute percentage error (MAPE) to determine the accuracy of each method.
Proceedings ArticleDOI
Iterative Learning-based Model Predictive Control for Precise Trajectory Tracking of Piezo Nanopositioning Stage
Shengwen Xie,Juan Ren +1 more
TL;DR: An iterative learning-based MPC (IL-MPC) algorithm is proposed in this paper to achieve accurate and high-efficacy trajectory tracking of nanopositioning devices through the integration of ILC and MPC.
Journal ArticleDOI
Investigative approaches to researching information technology companies
TL;DR: This work proposes investigation as a model for critical information studies and reviews the methods and epistemological conventions of investigative journalists as a provocative example, noting that their orientation toward those in power enables them to discuss societal harms in ways that academic researchers often cannot.