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Sparse Bayesian deep learning for dynamic system identification
Hongpeng Zhou
, Chahine Ibrahim
,
Wei Xing Zheng
, Wei Pan
Western Sydney University
School of Computer, Data & Mathematical Sciences
Research output
:
Contribution to journal
›
Article
›
peer-review
29
Citations (Scopus)
Overview
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Dive into the research topics of 'Sparse Bayesian deep learning for dynamic system identification'. Together they form a unique fingerprint.
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Weight
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Computer Science
System Identification
100%
Deep Neural Network
100%
Deep Learning Method
100%
Approximation (Algorithm)
40%
Bayesian Approach
40%
Experimental Result
20%
Linear Systems
20%
Identification Algorithm
20%
Identification Problem
20%
Nonlinear System Identification
20%
Marginal Likelihood
20%
Monte Carlo Integration
20%
Training Data
20%
Sparsity
20%
Engineering
Deep Learning Method
100%
Deep Neural Network
100%
Bayesian Approach
40%
Experimental Result
20%
Recursive
20%
Model Parameter
20%
Nonlinear System Identification
20%
Model Prediction
20%
Optimisation Procedure
20%
Integration Method
20%
Practical Calculation
20%
System Identification Problem
20%
Group Sparsity
20%
Uncertainty Quantification
20%
Regressors
20%
Chemical Engineering
Deep Learning Method
100%
Deep Neural Network
100%
Nonlinear System
20%
Linear Systems
20%