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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Proceedings ArticleDOI
Estimating polynomial structures from radar data
TL;DR: This work considers extended objects as extended objects modeled by polynomials along the road, and proposes an algorithm to track each polynomial based on noisy range and bearing detections, typically from a radar.
System identification with input uncertainties : an EM kernel-based approach
TL;DR: Many classical problems in system identification, such as the classical predictionerror method and regularized system Identification, identification of Hammerstein and cascaded systems, blind system ...
Journal ArticleDOI
Model- vs. data-based approaches applied to fault diagnosis in potable water supply networks
Miquel À. Cugueró-Escofet,Joseba Quevedo,Cesare Alippi,Manuel Roveri,Vicenç Puig,Diego Garcia,Francesco Trovò +6 more
TL;DR: Two different fault diagnosis approaches are proposed to deal with the problem of fault diagnosis in potable water supply networks, based on a model-based approach and a data-driven solution meant to exploit the spatial and temporal relationships present in the acquired data streams in order to detect and isolate faults.
Posted Content
Fundamental limitations of network reconstruction
TL;DR: It is found that reconstructing any property of the interaction Matrix is generically as difficult as reconstructing the interaction matrix itself, requiring equally informative temporal data.
Journal ArticleDOI
Photovoltaic Power Forecasting Model Based on Nonlinear System Identification
TL;DR: In this article, the identification of a PV system characteristic in the real-life environment in Kuwait is discussed and a Hammerstein-Wiener model is identified and selected due to its suitability to capture the PV system dynamics.