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
Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
TL;DR: A novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty, based on the idea of cooperative smoothing-the Bayesian extension of the leave-one-out cross-validation approach to model selection.
Journal ArticleDOI
Cardiovascular control in women with fibromyalgia syndrome: Do causal methods provide nonredundant information compared with more traditional approaches?
Antonio Roberto Zamunér,Alberto Porta,Carolina Pieroni Andrade,Andrea Marchi,Meire Forti,Raffaello Furlan,Franca Barbic,Aparecida Maria Catai,Ester da Silva +8 more
TL;DR: The model-based closed-loop approach proved to provide important complementary information about the cardiovascular autonomic control in patients with FMS by detecting lower BRS in supine position and a blunted response to the orthostatic stimulus.
Journal ArticleDOI
Health assessment of LFP automotive batteries using a fractional-order neural network
TL;DR: The state of health estimation produced by the fractional order network was consistently better than statistical and fuzzy models, LSTM and Echo State Networks for all the batteries under study.
Proceedings ArticleDOI
User friendly Box-Jenkins identification using nonparametric noise models
TL;DR: The identification of SISO linear dynamic systems in the presence of output noise disturbances is considered and a ‘nonparametric’ Box-Jenkins approach is studied: the parametric noise model is replaced by a nonparametric model that is obtained in a preprocessing step, and this without any user interaction.
Journal ArticleDOI
Parameter estimation in time-triggered and event-triggered model-based control of uncertain systems
Eloy Garcia,Panos J. Antsaklis +1 more
TL;DR: In this article on-line parameter estimation of dynamical systems is addressed in the context of model-based networked control systems (MB-NCSs) and stability conditions that are robust to parameter uncertainties and lack of feedback for extended intervals of time are presented.