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Use of the q-Gaussian mutation in evolutionary algorithms
(SPRINGER, 2011)
This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real ...
Coloring Non-Gaussian Sequences
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2008)
Probabilistic machine learning for detection of tightening torque in bolted joints
(2022-01-01)
Observing the loss of tightening torque using modal parameters is challenging due to the variability and nonlinear effects in bolted joints. Thus, this paper proposes a combined application of two probabilistic machine ...
Delamination area quantification in composite structures using Gaussian process regression and auto-regressive models
(2020-01-01)
After detecting initial delamination damage in a hotspot region of a composite structure monitored through a data-driven approach, the user needs to decide if there is an imminent structural failure or if the system can ...
Modeling neonatal EEG using multi-output Gaussian processes
(IEEE, 2022)
Neonatal seizures are sudden events in brain activity with detrimental effects in neurological functions usually related to epileptic fits. Though neonatal seizures can be identified from electroencephalography (EEG), this ...
Necessary And Sufficient Conditions For Surrogate Functions Of Pareto Frontiers And Their Synthesis Using Gaussian Processes
(IEEE-Inst Electrical Electronics Engineers IncPiscataway, 2017)
Performing edge detection by difference of Gaussians using q-Gaussian kernels
(Institute of Physics - IOPBristol, 2014)
In image processing, edge detection is a valuable tool to perform the extraction of features from an image. This detection reduces the amount of information to be processed, since the redundant information (considered less ...
Complete state reconstruction of a two-mode Gaussian state via local operations and classical communication
(Amer Physical SocCollege PkEUA, 2009)
Performing edge detection by difference of Gaussians using q-Gaussian kernels
(IOP PublishingBristol, 2014)
In image processing, edge detection is a valuable tool to perform the extraction of features from an image. This detection reduces the amount of information to be processed, since the redundant information (considered less ...
Controlling blood glucose variability under uncertainty using reinforcement learning and Gaussian processes
(Elsevier, 2015-06)
Automated control of blood glucose (BG) concentration with a fully automated artificial pancreas will certainly improve the quality of life for insulin-dependent patients. Closed-loop insulin delivery is challenging due ...