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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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Journal ArticleDOI

A data augmentation approach for a class of statistical inference problems.

TL;DR: An algorithm is presented to reformulate the inference problem as an optimization procedure, based on the generation of surrogate (auxiliary) functions, motivated by the MM algorithm, combined with the systematic and iterative structure of the Expectation-Maximization algorithm.
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An Interactive Computer-Aided Instructional Strategy and Assessment Methods for System Identification and Adaptive Control Laboratory

TL;DR: A benefit of this paper for engineering educators is that it provides a roadmap for transferring complex theory problems into prototypes in the laboratory, and can easily be adapted to other engineering courses.
Journal ArticleDOI

Elimination of impulsive disturbances from stereo audio recordings using vector autoregressive modeling and variable-order Kalman filtering

TL;DR: This paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings based on vector autoregressive modeling of audio signals based on the stability-preserving Whittle-Wiggins-Robinson algorithm.
Journal ArticleDOI

Identifiability of generalised Randles circuit models

TL;DR: In this article, the identifiability of generalised Randles circuit models is investigated, that is, whether the model parameters can be estimated uniquely from the input-output data.
Journal ArticleDOI

Direct C/GMRES Control of The Air Path of a Diesel Engine

TL;DR: In this paper, the authors apply a method which combines both worlds, the C/GMRES method, to a production Diesel engine and test against the production controller, showing the potential performance of the suggested method but also the design simplicity.