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
Generalized binary noise stimulation enables time-efficient identification of input-output brain network dynamics
Yuxiao Yang,Maryam M. Shanechi +1 more
TL;DR: A generalized binary noise modulated stimulation pattern is designed that achieves time-efficient identification of IO dynamics by utilizing the time-constant information of the network.
The Use of Bootstrap in System Identification
TL;DR: The main contribution is a proposed algorithm to estimate the probability density function in case of undermodeling to illustrate the performance of the bootstrap resampling method by simulation examples, which are in good agreement with Monte Carlo simulations.
Cryptographic Solutions for Cyber-Physical System Security
TL;DR: This dissertation will present an intrusion-tolerant and privacy-preserving sensor fusion scheme, a lightweight intrusion detection system for industrial control systems, and a multi-factor authenticated key exchange protocol based on historical data.
Proceedings ArticleDOI
Data Informativity for the Identification of MISO FIR Systems with Filtered White Noise Excitation
TL;DR: This paper proposes a necessary and sufficient condition for the data informativity in the case of multiple-inputs single-output finite impulse response model structure in open-loop.
Proceedings ArticleDOI
Adaptive Robust Kalman Filter for Vision-based Pose Estimation of Industrial Robots
TL;DR: The proposed adaptive robust Kalman filter (ARKF) exploits the advantages of adaptive estimation method for states noise covariance, least square identification for measurement noise covariancy and a robust mechanism for state variables error covariance to outperform above-mentioned methods both in smooth filtering and in signal tracking.