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gaussian process for a Single-channel EEG Decoder with Inconspicuous Stimuli and Eyeblinks

Computers, Materials & Continua 2022年第10期73卷 611-628页

作者： Nur Syazreen Ahmad Jia Hui Teo Patrick Goh School of Electrical&Electronic Engineering Universiti Sains MalaysiaNibong TebalPenang14300Malaysia

A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive brain-computer interface(BCI)applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles.In this study,a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control signal.The proposed decoder is constructed based on gaussian process model(GPM)which is a nonparametric Bayesian approach that has the advantages of being able to operate on small datasets and providing measurements of uncertainty on predictions.To evaluate the effectiveness of the proposed method,the GPM is compared against other competitive techniques which include k-Nearest Neighbors,linear discriminant analysis,support vector machine,ensemble learning and neural network.Results demonstrate that a significant improvement can be achieved via the GPM approach with average accuracy reaching over 96%and mean absolute error of no greater than 0.8 cm/s.In addition,the analysis reveals that while the performances of other existing methods deteriorate with a certain type of stimulus due to signal drifts resulting from the voluntary eyeblinks,the proposed GPM exhibits consistent performance across all stimuli considered,thereby manifesting its generalization capability and making it a more suitable option for dynamic commands with a single-channel EEG-controlled actuator.

关键词： Brain-computer interface dynamic command electroence phalography gaussian process model visual stimulus voluntary eyeblinks

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An adaptive sequential experiment design method for model validation

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Chinese Journal of Aeronautics 2020年第6期33卷 1661-1672页

作者： Ke FANG Yuchen ZHOU Ping MA Control and Simulation Center Harbin Institute of TechnologyHarbin 150080China

Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model.In this paper,an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed.The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points.To avoid the clustering of samples in the local region,an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation.Besides,the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design.Finally,six benchmark problems and an engineering case are applied to examine the performance of the proposed method.The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.

关键词： Adaptive sequential experiment design Credibility distribution function gaussian process model Metamodeling model validation

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CONSTRUCTION OF IMPROVED BRANCHING LATIN HYPERCUBE DESIGNS

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Acta Mathematica Scientia 2021年第4期41卷 1023-1033页

作者：陈浩杨金语刘民千 School of Statistics Tianjin University of Finance and EconomicsTianjin 300222China School of Statistics and Data Science LPMC&KLMDASRNankai UniversityTianjin 300071China

In this paper,we propose a new method,called the level-collapsing method,to construct branching Latin hypercube designs(BLHDs).The obtained design has a sliced structure in the third part,that is,the part for the shared factors,which is desirable for the qualitative branching factors.The construction method is easy to implement,and(near)orthogonality can be achieved in the obtained BLHDs.A simulation example is provided to illustrate the effectiveness of the new designs.

关键词： Branching and nested factors computer experiment gaussian process model orthogonality

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Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization

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Open Journal of Statistics 2016年第3期6卷 528-544页

作者： Pritam Ranjan Mark Thomas Holger Teismann Sujay Mukhoti OM & QT Indian Institute of Management Indore Indore India Department of Mathematics & Statistics Acadia University Wolfville Canada

For an expensive to evaluate computer simulator, even the estimate of the overall surface can be a challenging problem. In this paper, we focus on the estimation of the inverse solution, i.e., to find the set(s) of input combinations of the simulator that generates a pre-determined simulator output. Ranjan et al. [1] proposed an expected improvement criterion under a sequential design framework for the inverse problem with a scalar valued simulator. In this paper, we focus on the inverse problem for a time-series valued simulator. We have used a few simulated and two real examples for performance comparison.

关键词： Calibration Computer Experiments Contour Estimation gaussian process model Non-Stationary process Sequential Design

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