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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.
Journal ArticleDOI

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.
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.
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Regret Minimization in Partially Observable Linear Quadratic Control

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Platform-Centric Self-Awareness as a Key Enabler for Controlling Changes in CPS

TL;DR: It is argued that seemingly unrelated research challenges, such as in machine learning and security, could also profit from the methods and superior modeling capabilities of self-aware systems.
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Bias-Compensated Least Squares Identification of Distributed Thermal Models for Many-Core Systems-on-Chip

TL;DR: This work proposes a novel distributed identification strategy to derive distributed interacting thermal models that can cope with both process noise and temperature sensor noise affecting inputs and outputs of the adopted models.
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A novel hybrid bacteria-chemotaxis spiral-dynamic algorithm with application to modelling of flexible systems

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Structural vs Practical Identifiability in System Biology.

TL;DR: The relevance of model identiability structural identiability is still relevant and does not require to use data collected in the exper- iment which, instead, data-based approaches do.