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
Citations
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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
A procedure for modeling buildings and their thermal zones using co-simulation and system identification
TL;DR: In this paper, a university building is first modeled using EnergyPlus, an energy simulation software, and then validated using measured temperatures in the university building, which is then used to generate informative input/output data to perform system identification techniques.
Journal ArticleDOI
Sparse Estimation of Polynomial and Rational Dynamical Models
TL;DR: A new technique for sparse linear regression called SPARSEVA is proposed, with close ties with the LASSO, which provides an automatic tuning of the amount of regularization, which imposes a severe constraint on the types of model structures or estimation methods on which the ℓ1 relaxation can be applied.
Journal ArticleDOI
Adaptive Bayesian Learning and Forecasting of Epidemic Evolution—Data Analysis of the COVID-19 Outbreak
Domenico Gaglione,Paolo Braca,Leonardo M. Millefiori,Giovanni Soldi,Nicola Forti,Stefano Marano,Peter Willett,Krishna R. Pattipati +7 more
TL;DR: It is shown that the proposed method is able to estimate infection and recovery parameters, and to track and predict the epidemiological curve with good accuracy when applied to real data from Lombardia region in Italy, and from the USA.
Proceedings ArticleDOI
A sparsity based GLRT for moving target detection in distributed MIMO radar on moving platforms
Zhe Wang,Hongbin Li,Braham Himed +2 more
TL;DR: Numerical results indicate that the proposed training-free detectors offer improved detection performance over covariance matrix based detectors when the latter have a moderate amount of training signals.
Rao-Blackwellised particle methods for inference and identification
TL;DR: This work considers the two related problems of state inference in nonlinear dynamical systems and nonlinear system identification based on noisy observations from some (in general) nonlin systems.